{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c979f719-a7bd-4392-86f9-f699220b2c93",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATEFP20</th>\n",
       "      <th>COUNTYFP20</th>\n",
       "      <th>TRACTCE20</th>\n",
       "      <th>GEOID20</th>\n",
       "      <th>NAME20</th>\n",
       "      <th>NAMELSAD20</th>\n",
       "      <th>MTFCC20</th>\n",
       "      <th>FUNCSTAT20</th>\n",
       "      <th>ALAND20</th>\n",
       "      <th>AWATER20</th>\n",
       "      <th>...</th>\n",
       "      <th>P0050002</th>\n",
       "      <th>P0050003</th>\n",
       "      <th>P0050004</th>\n",
       "      <th>P0050005</th>\n",
       "      <th>P0050006</th>\n",
       "      <th>P0050007</th>\n",
       "      <th>P0050008</th>\n",
       "      <th>P0050009</th>\n",
       "      <th>P0050010</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>51</td>\n",
       "      <td>085</td>\n",
       "      <td>320100</td>\n",
       "      <td>51085320100</td>\n",
       "      <td>3201</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>328537534</td>\n",
       "      <td>2927606</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-77.74029 37.87408, -77.73998 37.874...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>085</td>\n",
       "      <td>321201</td>\n",
       "      <td>51085321201</td>\n",
       "      <td>3212.01</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>11255521</td>\n",
       "      <td>16144</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>POLYGON ((-77.36115 37.60754, -77.36084 37.607...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>51</td>\n",
       "      <td>085</td>\n",
       "      <td>321202</td>\n",
       "      <td>51085321202</td>\n",
       "      <td>3212.02</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>8887075</td>\n",
       "      <td>96758</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-77.38286 37.59526, -77.38280 37.595...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>51</td>\n",
       "      <td>085</td>\n",
       "      <td>320400</td>\n",
       "      <td>51085320400</td>\n",
       "      <td>3204</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>58245255</td>\n",
       "      <td>348336</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-77.61233 37.75986, -77.61216 37.760...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>51</td>\n",
       "      <td>810</td>\n",
       "      <td>045000</td>\n",
       "      <td>51810045000</td>\n",
       "      <td>450</td>\n",
       "      <td>Census Tract</td>\n",
       "      <td>G5020</td>\n",
       "      <td>S</td>\n",
       "      <td>21420965</td>\n",
       "      <td>29350</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1050</td>\n",
       "      <td>0</td>\n",
       "      <td>1050</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON ((-76.06314 36.80147, -76.06114 36.802...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 345 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  STATEFP20 COUNTYFP20 TRACTCE20      GEOID20   NAME20    NAMELSAD20 MTFCC20  \\\n",
       "0        51        085    320100  51085320100     3201  Census Tract   G5020   \n",
       "1        51        085    321201  51085321201  3212.01  Census Tract   G5020   \n",
       "2        51        085    321202  51085321202  3212.02  Census Tract   G5020   \n",
       "3        51        085    320400  51085320400     3204  Census Tract   G5020   \n",
       "4        51        810    045000  51810045000      450  Census Tract   G5020   \n",
       "\n",
       "  FUNCSTAT20    ALAND20  AWATER20  ... P0050002 P0050003 P0050004 P0050005  \\\n",
       "0          S  328537534   2927606  ...        0        0        0        0   \n",
       "1          S   11255521     16144  ...        0        0        0        0   \n",
       "2          S    8887075     96758  ...        0        0        0        0   \n",
       "3          S   58245255    348336  ...        0        0        0        0   \n",
       "4          S   21420965     29350  ...        0        0        0        0   \n",
       "\n",
       "  P0050006 P0050007 P0050008 P0050009 P0050010  \\\n",
       "0        0        0        0        0        0   \n",
       "1        0       15        0        0       15   \n",
       "2        0        0        0        0        0   \n",
       "3        0        0        0        0        0   \n",
       "4        0     1050        0     1050        0   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((-77.74029 37.87408, -77.73998 37.874...  \n",
       "1  POLYGON ((-77.36115 37.60754, -77.36084 37.607...  \n",
       "2  POLYGON ((-77.38286 37.59526, -77.38280 37.595...  \n",
       "3  POLYGON ((-77.61233 37.75986, -77.61216 37.760...  \n",
       "4  POLYGON ((-76.06314 36.80147, -76.06114 36.802...  \n",
       "\n",
       "[5 rows x 345 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# this is for working with census tracts and VTD precincts\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "import shapely\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "import math\n",
    "import time\n",
    "tractPopFile = gpd.read_file(\"../state_map_files/va_pl2020_t.dbf\") #for Texas, need only this file\n",
    "tractPopFile.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "3e4af1be-0f6a-4c46-9d23-da70d63c30e8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly):\n",
    "    simplePoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == simplePoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "def r3(x):\n",
    "    result = round(x,3)\n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a7a90b04-4b48-4ab8-9195-8d953907c3fb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 2198 popn tracts for VA\n"
     ]
    }
   ],
   "source": [
    "# EXTRACT TRACT GEOMETRIES AND POPULATIONS INTO LISTS, COMPUTE TRACT AREAS\n",
    "# If the population and geometry data are in one file, this should work.\n",
    "STATE = \"VA\"\n",
    "tractGeom = tractPopFile['geometry']  #for some states, replace with tractGeomFile\n",
    "tractPop = tractPopFile['P0010001']\n",
    "tractVAP = tractPopFile['P0030001']   #NEW 3/2/22 - USE VAP\n",
    "# tractPop2 = tractPopFile['P0020001']   #not needed; confirmed that this matches P00100001 exactly\n",
    "tractHisp = tractPopFile['P0040002']   #NEW 3/2/22 - USE VAP\n",
    "tractBlack = tractPopFile['P0030004']  #NEW 3/2/22 - USE VAP\n",
    "nTracts = len(tractPop)\n",
    "print(\"there are {0} popn tracts for {1}\".format(nTracts, STATE) )\n",
    "tractArea = [0.]*nTracts\n",
    "for t in range (0,nTracts) :\n",
    "    tractArea[t] = tractGeom[t].area\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation\n",
    "tractPop = tractPop.to_numpy()  #to avoid panda overwrite grousing\n",
    "tractBlack= tractBlack.to_numpy()\n",
    "tractHisp = tractHisp.to_numpy()\n",
    "tractVAP = tractVAP.to_numpy()\n",
    "stateVAP = np.sum(tractVAP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c90b3908-e2e3-46b8-98e5-ae285eca1ee3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is Hispanic population by total population VA voter-age population\n",
      "state pop= 8631393 VAP pct Hispanic is  0.09107621673599647\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our correlation of Hispanic pop to total pop?\n",
    "print(\"this is Hispanic population by total population \"+STATE,\"voter-age population\")\n",
    "print(\"state pop=\",np.sum(tractPop), \"VAP pct Hispanic is \",np.sum(tractHisp)/np.sum(tractVAP) )\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"tract Voter Age Population\", ylabel=\"tract Hispanic pop\")\n",
    "x = [0,10000]\n",
    "y = [0,10000]\n",
    "plt.plot(tractVAP, tractHisp, marker='.',linestyle=\"none\")\n",
    "plt.plot(x,y,linestyle = 'dashed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "237df16d-af87-47ba-acb1-2ef5702c1406",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is voter-age Black population by total VAP VA\n",
      "total state pop= 8631393 , VAP pct Black is  0.18414159471517944\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our correlation of Black pop to total pop?\n",
    "print(\"this is voter-age Black population by total VAP \"+STATE)\n",
    "print(\"total state pop=\",np.sum(tractPop), \", VAP pct Black is \",np.sum(tractBlack)/np.sum(tractVAP) )\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"tract VAP\", ylabel=\"tract Black VAP\")\n",
    "x = [0,10000]\n",
    "y = [0,10000]\n",
    "plt.plot(tractVAP, tractBlack, marker='.',linestyle=\"none\")\n",
    "plt.plot(x,y,linestyle = 'dashed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "10b208af-8eb0-45fa-9dc0-8873eb797200",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of Census tract population for VA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#for curiosity, let's plot the distribution of populations among tracts\n",
    "n_bins=50\n",
    "print(\"this is a histogram of Census tract population for \"+STATE)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractPop, bins=n_bins)\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4aac60d6-4cce-469b-b075-ad743acda38c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is population by Census tract for VA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our distribution of tract populations by area?\n",
    "print(\"this is population by Census tract for \"+STATE)  \n",
    "plt.plot(tractPop, tractArea, marker='.',linestyle=\"none\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f159bf55-a25e-45c0-b7ea-4c21fbce9bb0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'shapely.geometry.polygon.Polygon'> <class 'shapely.geometry.polygon.Polygon'>\n"
     ]
    }
   ],
   "source": [
    "print( type(tractGeom[0]),type(tractGeom[1]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5e8f8f92-a336-43e5-8ac5-20c657cb5857",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "looking for nonPolygons in census tract data\n",
      "533 5713 0.0014730299864999352 nonPolygon tract no, pop, area\n",
      "1.7997562499985003e-05\n",
      "0.0014550324239999502\n",
      "760 3124 0.00030674889250008715 nonPolygon tract no, pop, area\n",
      "1.2578714499983114e-05\n",
      "1.413166550003769e-05\n",
      "0.00028003851250006634\n",
      "934 5839 0.0013355627229999897 nonPolygon tract no, pop, area\n",
      "0.0013176135669999975\n",
      "1.7949155999992245e-05\n",
      "1003 4403 0.012531170441999926 nonPolygon tract no, pop, area\n",
      "9.948219999962645e-07\n",
      "0.01253017561999993\n",
      "1021 4985 0.02334328910050007 nonPolygon tract no, pop, area\n",
      "5.908310500009416e-06\n",
      "0.02333738079000006\n",
      "1466 6569 0.022479768638000035 nonPolygon tract no, pop, area\n",
      "1.007071950000228e-05\n",
      "0.02246564745900003\n",
      "4.050459500001525e-06\n",
      "1488 1836 0.04494380089950007 nonPolygon tract no, pop, area\n",
      "0.04491284240100008\n",
      "1.432920049998585e-05\n",
      "1.6629298000005914e-05\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"looking for nonPolygons in census tract data\")\n",
    "notPoly = [0]*nTracts\n",
    "for m in range(nTracts):\n",
    "    if type(tractGeom[m]) != type(tractGeom[1]):  #assuming tract 1 is a single polygon\n",
    "        notPoly[m] = 1\n",
    "        print(m,tractPop[m], tractArea[m], \"nonPolygon tract no, pop, area\")\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        if y < 999 :  #let's zoom in on these\n",
    "            for geom in tractGeom[m].geoms :\n",
    "                xg,yg = geom.exterior.xy\n",
    "                print(geom.area)\n",
    "                plt.plot(xg,yg)\n",
    "            plt.text(x+0.0,y+0.01,m,fontsize=9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d34b5fe5-6f02-413a-8c7b-c6662fa756ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#convex-hull these right away  (decision for each state - YES for VA)\n",
    "for m in range(nTracts):\n",
    "    if notPoly[m] == 1:\n",
    "        for geom in tractGeom[m].geoms :\n",
    "            xg,yg = geom.exterior.xy\n",
    "            plt.plot(xg,yg)\n",
    "        tractGeom[m] = tractGeom[m].convex_hull\n",
    "        x,y = tractGeom[m].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "        notPoly[m] = 0\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a05c0ec2-d208-45b8-8ff6-c1f1f583ad5d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[79, 1270, 1503, 1508, 2162]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For potential later issues, identify and flag lakeshore low-population tracts.\n",
    "isSkippedTract = [0]*nTracts\n",
    "lakeTracts = [9999]\n",
    "minTractPop = 20\n",
    "for m in range(nTracts):\n",
    "    if tractPop[m] < minTractPop:\n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        if y < 999 and x > -999 : #optional to exclude some areas from plotting\n",
    "            plotPoly(tractGeom[m])\n",
    "        #plt.scatter(x,y)\n",
    "        if x > -76 :            \n",
    "            plt.text(x, y+0.00,m, fontsize=9)\n",
    "            if lakeTracts == [9999]:\n",
    "                lakeTracts = [m]\n",
    "                isSkippedTract[m] = 1\n",
    "            else:\n",
    "                if 0 ==0 :  #m==99940 or m==999909:\n",
    "                    lakeTracts.append(m)\n",
    "                    isSkippedTract[m] = 1\n",
    "                else:\n",
    "                    thisTract = \"interior\"\n",
    "                    \n",
    "\n",
    "print(lakeTracts)  # assigned as skipped tracts as well\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b0e9e246-a558-475c-8181-075a9421034e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2198 5\n"
     ]
    }
   ],
   "source": [
    "print(len(isSkippedTract),np.sum(isSkippedTract))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d63968a2-afc1-4913-863c-4c415fb9c0b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "looking for tracts with zero area\n"
     ]
    }
   ],
   "source": [
    "# For potential later issues, identify and visualize zero-Area tracts.  See Ohio code for more code\n",
    "isSkippedTract = [0]*nTracts\n",
    "print(\"looking for tracts with zero area\")\n",
    "for m in range(nTracts):\n",
    "    if(tractArea[m] == 0):       \n",
    "        x = tractGeom[m].centroid.x\n",
    "        y = tractGeom[m].centroid.y\n",
    "        print( m,tractPop[m],\"(\",x,\",\",y,\")\" )\n",
    "        x2,y2 = tractGeom[m].exterior.xy\n",
    "        plt.plot(x2,y2,c=\"purple\")\n",
    "        #print(tractGeom[m])\n",
    "        plt.scatter(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "72abde7f-085d-4c0a-abe3-29e8d6203b40",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNTYFP</th>\n",
       "      <th>LOCALITY</th>\n",
       "      <th>VTDST</th>\n",
       "      <th>PRECINCT</th>\n",
       "      <th>G20PREDBID</th>\n",
       "      <th>G20PRERTRU</th>\n",
       "      <th>G20PRELJOR</th>\n",
       "      <th>G20PREOWRI</th>\n",
       "      <th>G20USSDWAR</th>\n",
       "      <th>G20USSRGAD</th>\n",
       "      <th>G20USSOWRI</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>000101</td>\n",
       "      <td>Chincoteague</td>\n",
       "      <td>837</td>\n",
       "      <td>1618</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>915</td>\n",
       "      <td>1563</td>\n",
       "      <td>3</td>\n",
       "      <td>POLYGON Z ((-75.42507 37.89957 0.00000, -75.42...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>001</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>000201</td>\n",
       "      <td>Atlantic</td>\n",
       "      <td>321</td>\n",
       "      <td>657</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>357</td>\n",
       "      <td>644</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON Z ((-75.59978 37.87664 0.00000, -75.59...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>001</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>000202</td>\n",
       "      <td>Greenbackville</td>\n",
       "      <td>516</td>\n",
       "      <td>1091</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>539</td>\n",
       "      <td>1054</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON Z ((-75.49919 37.93416 0.00000, -75.49...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>001</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>000301</td>\n",
       "      <td>New Church</td>\n",
       "      <td>1013</td>\n",
       "      <td>667</td>\n",
       "      <td>14</td>\n",
       "      <td>2</td>\n",
       "      <td>1003</td>\n",
       "      <td>638</td>\n",
       "      <td>2</td>\n",
       "      <td>POLYGON Z ((-75.64987 37.92702 0.00000, -75.64...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>001</td>\n",
       "      <td>Accomack County</td>\n",
       "      <td>000401</td>\n",
       "      <td>Bloxom</td>\n",
       "      <td>307</td>\n",
       "      <td>462</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>306</td>\n",
       "      <td>447</td>\n",
       "      <td>0</td>\n",
       "      <td>POLYGON Z ((-75.71556 37.87513 0.00000, -75.71...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  COUNTYFP         LOCALITY   VTDST        PRECINCT  G20PREDBID  G20PRERTRU  \\\n",
       "0      001  Accomack County  000101    Chincoteague         837        1618   \n",
       "1      001  Accomack County  000201        Atlantic         321         657   \n",
       "2      001  Accomack County  000202  Greenbackville         516        1091   \n",
       "3      001  Accomack County  000301      New Church        1013         667   \n",
       "4      001  Accomack County  000401          Bloxom         307         462   \n",
       "\n",
       "   G20PRELJOR  G20PREOWRI  G20USSDWAR  G20USSRGAD  G20USSOWRI  \\\n",
       "0          29           2         915        1563           3   \n",
       "1          11           2         357         644           0   \n",
       "2          18           0         539        1054           0   \n",
       "3          14           2        1003         638           2   \n",
       "4           8           0         306         447           0   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON Z ((-75.42507 37.89957 0.00000, -75.42...  \n",
       "1  POLYGON Z ((-75.59978 37.87664 0.00000, -75.59...  \n",
       "2  POLYGON Z ((-75.49919 37.93416 0.00000, -75.49...  \n",
       "3  POLYGON Z ((-75.64987 37.92702 0.00000, -75.64...  \n",
       "4  POLYGON Z ((-75.71556 37.87513 0.00000, -75.71...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Now, let's read in the voting data  \n",
    "VTDdbf = gpd.read_file(\"../state_map_files/va_vest_20.dbf\")\n",
    "VTDdbf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "4f3b9ddb-b971-472c-a353-521377f95e46",
   "metadata": {},
   "outputs": [],
   "source": [
    "#VTDdbf = VTDdbf.to_crs(tractPopFile.crs)  #MD's precinct file in wrong CRS\n",
    "#VTDdbf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3fe4ceba-8077-4485-ad0a-f8f2a5755040",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2477 0.4484531300060009 4375998 = number of precincts, statewide GOP vote, total Trump+Biden votes\n"
     ]
    }
   ],
   "source": [
    "# Pull VTD geopandas data columns into arrays\n",
    "vtdGeom = VTDdbf['geometry'] \n",
    "# vtdGeom = VTDdbf['geometry'] #can't use VTDdbf because it uses alternate coordinate system\n",
    "vtdTrump = VTDdbf['G20PRERTRU']\n",
    "vtdBiden = VTDdbf['G20PREDBID']\n",
    "\n",
    "nPrecincts = len(vtdGeom)\n",
    "stateGOP = np.sum(vtdTrump)/(np.sum(vtdTrump) + np.sum(vtdBiden) ) \n",
    "print(nPrecincts, stateGOP, np.sum(vtdTrump) + np.sum(vtdBiden),\n",
    "      \"= number of precincts, statewide GOP vote, total Trump+Biden votes\" )\n",
    "vtdTrump = vtdTrump.to_numpy()  #these two lines try to avoid pandas complaints when we overwrite precinct data\n",
    "vtdBiden = vtdBiden.to_numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c5c57f52-b8d2-4ef4-9d02-2429ed5e59da",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#ID the non-polygon PRECINCTS\n",
    "notPolyVTD = [0]*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    if type(vtdGeom[p]) != type(vtdGeom[0]):\n",
    "        notPolyVTD[p] = 1\n",
    "        plotPoly(vtdGeom[p])\n",
    "        #plt.text(vtdGeom[p].centroid.x, vtdGeom[p].centroid.y,p)\n",
    "    else:\n",
    "        hi = \"hi\"\n",
    "        #x,y = vtdGeom[p].exterior.xy\n",
    "        #plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ea498c6a-d054-409e-92fb-cda921e2911f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#prep for geography triage\n",
    "#isSkippedTract = [0]*nTracts  #done above; already skipped two lakeshore tracts\n",
    "isSkippedPrecinct = [0]*nPrecincts  #will be used later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3ded1b1f-5629-4d8f-826b-e037e5dcb3da",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 300\n",
      "working on tract 600\n",
      "working on tract 900\n",
      "working on tract 1200\n",
      "working on tract 1500\n",
      "working on tract 1800\n",
      "working on tract 2100\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#build basic VA map\n",
    "tractMAP = tractGeom[0] #uncomment for first time thru loop  **************\n",
    "for t in range(1,nTracts):\n",
    "    if t%300 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if isSkippedTract[t] == 0:\n",
    "        uncomment = \"if-redone\"\n",
    "        tractMAP = tractMAP.union(tractGeom[t])  #uncomment to build map  ********\n",
    "plotPoly(tractMAP)\n",
    "pt1 = Point(-83.75,36.5)\n",
    "pt2 = Point(-81.6,36.5)\n",
    "pt3 = Point(-81.1,37.6)\n",
    "pt4 = Point(-83.75,37.6)\n",
    "clipPoly = Polygon([pt1,pt2,pt3,pt4])  #first outcropping we wish to move in\n",
    "plotPoly(clipPoly)\n",
    "\n",
    "plt.show()\n",
    "wholeMAP = tractMAP  #in case we later slice parts out\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f33de347-5473-4b11-b3ae-86691b33098d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have flagged  85 tracts w pop 280915.0  to reassign to tracts...\n",
      "[176, 326, 1107, 1460, 1779]\n",
      "I have flagged  150 precincts to reassign to precincts...\n",
      "[180, 717, 718, 719, 721, 1453, 1454, 1457, 2016]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find all tracts and precincts centered in this clipPoly, flag for cutting\n",
    "# and, ID all nearby tracts and precincts to receive their pops and voters\n",
    "\n",
    "cutTractList = [-99999]\n",
    "cutPrecinctList = [-99999]\n",
    "tractReceivers = [-88888]\n",
    "precinctReceivers = [-88888]\n",
    "popToCut = 0.\n",
    "for t in range(nTracts):\n",
    "    x = tractGeom[t].centroid.x\n",
    "    y = tractGeom[t].centroid.y\n",
    "    if tractGeom[t].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedTract[t] = 1\n",
    "            popToCut += tractPop[t]\n",
    "            if cutTractList == [-99999]:\n",
    "                cutTractList = [t]\n",
    "            else:\n",
    "                cutTractList.append(t)\n",
    "            x,y = tractGeom[t].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        if tractGeom[t].distance(clipPoly) < 0.15 :  # and tractGeom[t].centroid.x > -76.4 :\n",
    "            if tractReceivers == [-88888]:\n",
    "                tractReceivers = [t]\n",
    "            else:\n",
    "                tractReceivers.append(t)\n",
    "xp,yp = clipPoly.exterior.xy\n",
    "plt.plot(xp,yp)\n",
    "\n",
    "for p in range(nPrecincts):\n",
    "    x = vtdGeom[p].centroid.x\n",
    "    y = vtdGeom[p].centroid.y\n",
    "    if vtdGeom[p].intersects(clipPoly) :  #As of 3/19/22 - Virginia -- if ANY part of precinct intersects\n",
    "        isSkippedPrecinct[p] = 1  #then it's a skipped precinct, so we have no offmap precinct parts\n",
    "        if cutPrecinctList == [-99999]:\n",
    "            cutPrecinctList = [p]\n",
    "        else:\n",
    "            cutPrecinctList.append(p)\n",
    "    else:\n",
    "        if vtdGeom[p].distance(clipPoly) < 0.15 : # and vtdGeom[p].centroid.x > -76.4 :\n",
    "            if precinctReceivers == [-88888]:\n",
    "                precinctReceivers = [p]\n",
    "            else:\n",
    "                precinctReceivers.append(p)\n",
    "print(\"I have flagged \",len(cutTractList),\"tracts w pop\",popToCut,\" to reassign to tracts...\")\n",
    "print(tractReceivers)\n",
    "print(\"I have flagged \",len(cutPrecinctList),\"precincts to reassign to precincts...\")\n",
    "print(precinctReceivers)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "33897c0d-3254-4a76-9b82-314a8f320eaa",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 2 of 4\n",
    "#visualize the to-be-cut precincts, just to confirm there are really xx precincts up there\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] ==1:\n",
    "        if notPolyVTD[p]==1:\n",
    "            for geom in vtdGeom[p].geoms:\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y)\n",
    "        else:\n",
    "            x,y = vtdGeom[p].exterior.xy\n",
    "            plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e2595c62-579a-4af1-9552-0859524782be",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 3 of 4\n",
    "#now visualize the PRECINCT receivers\n",
    "for pp in range(len(precinctReceivers)):\n",
    "    p = precinctReceivers[pp]\n",
    "    if notPolyVTD[p]==1:\n",
    "        for geom in vtdGeom[p].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = vtdGeom[p].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9e1d7fcd-cdeb-4317-9f89-5291a9595587",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now visualize the TRACT receivers\n",
    "for tt in range(len(tractReceivers)):\n",
    "    t = tractReceivers[tt]\n",
    "    if notPoly[t]==1:\n",
    "        for geom in tractGeom[t].geoms:\n",
    "            x,y = geom.exterior.xy\n",
    "            plt.plot(x,y)\n",
    "    else:\n",
    "        x,y = tractGeom[t].exterior.xy\n",
    "        plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d2622568-1fc9-4089-9ae4-2550ea6fbaaf",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have finished slicing  280915.0 people (VAP of 227539.0 ) and  141241.0 voters out.\n"
     ]
    }
   ],
   "source": [
    "#now, cut and redistribute\n",
    "cutPop = 0.\n",
    "cutVAP = 0.\n",
    "cutHisp = 0.\n",
    "cutBlack = 0.\n",
    "cutTrump = 0.\n",
    "cutBiden = 0.\n",
    "\n",
    "for ct in range(len(cutTractList)):\n",
    "    t = cutTractList[ct]\n",
    "    cutPop += tractPop[t]  #sum up the cut pops\n",
    "    cutVAP += tractVAP[t]\n",
    "    cutHisp += tractHisp[t]\n",
    "    cutBlack += tractBlack[t]\n",
    "    # Now we zero out the pops in the cut tracts\n",
    "    tractPop[t] = 0\n",
    "    tractVAP[t] = 0\n",
    "    tractHisp[t] = 0\n",
    "    tractBlack[t] = 0\n",
    "# Now distribute the pops among the receivers\n",
    "ntR = len(tractReceivers)\n",
    "NTR = float(ntR)\n",
    "for rt in range(ntR) :\n",
    "    t = tractReceivers[rt]\n",
    "    tractPop[t] += cutPop/NTR\n",
    "    tractVAP[t] += cutVAP/NTR\n",
    "    tractHisp[t] += cutHisp/NTR\n",
    "    tractBlack[t] += cutBlack/NTR\n",
    "\n",
    "#             now do the same for the precincts\n",
    "for cp in range(len(cutPrecinctList)):\n",
    "    p = cutPrecinctList[cp]\n",
    "    cutTrump += vtdTrump[p]\n",
    "    cutBiden += vtdBiden[p]\n",
    "        # Now we zero out the pops in the cut precincts\n",
    "    vtdTrump[p] = 0\n",
    "    vtdBiden[p] = 0\n",
    "\n",
    "# Now distribute the pops among the receivers\n",
    "npR = len(precinctReceivers)\n",
    "NPR = float(npR)\n",
    "for rp in range(npR) :\n",
    "    p = precinctReceivers[rp]\n",
    "    vtdTrump[p] += cutTrump/NPR\n",
    "    vtdBiden[p] += cutBiden/NPR\n",
    "print(\"I have finished slicing \",cutPop,\"people (VAP of\",cutVAP,\") and \",cutBiden+cutTrump,\"voters out.\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fe47f683-719d-4a02-9648-905bddbf28a3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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qXB3IYDCg1+spKSkhLMxz+4yFEJ7pwQ8y+OZgPr3iQvjil6Odrizr7rILK3hu1X62HCug2lL/Y2N0z2j+OWNoi2YkCd/W3M9vSViEEKKV9p4pZtqb36NRq1j5i1H076R3dUjtJqe4kq/25bJ6fy7HL5RjVRRKq8yO/U+M78Xj43u6MELhaZr7+S1dQkII0UqLNhwHYNrARK9OVsBWUO7BMd14cEw3x7adJ4u44+1tALy67ghT0uLpEeua2jPCe3lXm6UQQnSwzDPFrLHPnvn5mO4ujsY1hnWN5MifJjMkJQKA2e9n8EP2RRdHJbyNUwnLokWLSEtLIywsjLCwMNLT01m9erVjf35+Pvfeey+JiYkEBQUxadIkjh492uR5ly9fTmpqKjqdjtTUVFasWOH8lQghhAtknCpy3E+OdH6RQW+h9VPz1t2DiQ3Vcbqwgp/+YxuZZ4pdHZbwIk4lLElJSSxYsICMjAwyMjIYN24c06ZN48CBAyiKws0338yJEydYuXIle/bsISUlhfHjx1NeXt7gObdt28b06dOZMWMGe/fuZcaMGdxxxx3s2LGj1RcnhBDt7bbBSY77NV1DviouLIDVj4+mW3QwFqvCzpMyBVq0nVYPuo2MjOTll19m9OjR9O7dm/3799OvXz8ALBYLsbGxvPTSSzzwwANXfP706dMxGAx1WmomTZpEREQES5cubXYcMuhWCOEKZouVPs+swWxVeHJCL351vQw4HfOX9WQXVfCPewYzqX+Cq8MRbq65n98tHsNisVhYtmwZ5eXlpKenYzQaAQgICHAco9Fo0Gq1bNmypcHzbNu2jRtuuKHOtokTJ7J169ZGX99oNGIwGOrchBCio32eeQ6zVSE8yJ97R3VxdTguV1JZTXZRBQAje0S7OBrhTZxOWLKysggJCUGn0/Hwww+zYsUKUlNT6dOnDykpKcyZM4eLFy9iMplYsGABeXl55ObmNni+vLw84uLi6myLi4sjL6/xEtDz589Hr9c7bsnJyc5eihBCtJjFqqAoCp/uOgPAg6O7ERbg7+KoXC9E50ewvRbLj+fki6RoO04nLL179yYzM5Pt27fzyCOPMGvWLA4ePIi/vz/Lly/nyJEjREZGEhQUxIYNG5g8eTIaTeOFhFQqVZ3HiqLU23a5OXPmUFJS4ridOXPG2UsRQogW2Xe2mCF/+oauc75ip33Q7S2DOrk4KvegUasY0ysGgOn/3E5VtcXFEQlv4XQdFq1WS48ePQAYOnQou3bt4vXXX+ftt99myJAhZGZmUlJSgslkIiYmhuHDhzN06NAGzxcfH1+vNeX8+fP1Wl0up9Pp0Ol0zoYvhBCt9tjHeyiuqHY8HtYlksRw350hdLnJVyWwer/t7/rNb37PrYM7UVZl5q7hnUnQy89JtEyr67AoiuIYv1JDr9cTExPD0aNHycjIYNq0aQ0+Pz09nW+++abOtrVr1zJy5MjWhiaEEG1u7YE8xxiNGjdL60odN6UlMKhzOACH8kr581eHWPjdMdLnf8fXsuKzaCGnWljmzp3L5MmTSU5OprS0lGXLlrFhwwbWrFkDwGeffUZMTAydO3cmKyuLxx9/nJtvvrnOoNqZM2fSqVMn5s+fD8Djjz/OmDFjeOmll5g2bRorV65k3bp1jQ7UFUIIV1mZec5xv1N4IGo13DE0qZFn+B6VSsWKR0exMjOHD7ad5kxRBedLbV9s5/43i2t7xRDgL2sOCec4lbDk5+czY8YMcnNz0ev1pKWlsWbNGiZMmABAbm4uTz75JPn5+SQkJDBz5kyeeeaZOufIzs5Grb7UsDNy5EiWLVvG008/zTPPPEP37t355JNPGD58eBtcnhBCtJ1yo5kNh88DsPyRdK7qFI6fWoVa3fiYO181bWAnpg20tT4ZzRau/csG8gxVrD90nslXyXRn4RxZ/FAIIRqhKApvbzqBzk9NsNaP3y/fR5eoINb/9romJweIul744iCLt5xkaloCf//ZYFeHI9yELH4ohBCtZLUq/Pyj3XxzMB+AbtHBAEy/urMkKy1w88BOLN5yktX788gprqSTDFQWTpDFD4UQogFfZOU6khWAEwXl6PzU3DZEBtm2xFVJetK7RWGxKny0/bSrwxEeRhIWIYRowDubT9Tb9vSUvsSGBlzhaNEcNdWAl+7MlhotwimSsAghxBUUlBk5eFml1r4JYdwzIsVFEXmH8X3j6BQeSHFFNTe/+X29n7EQDZGERQghLmM0W5i9ZBdmq0LnyCD6xIcyMDmclb8YJWNXWkmjVvH0lL5o/dQcyivlmZX7XR2S8BAy6FYIIS7zjw0n2Hu2BK1GzavTBzLYXgRNkpW2MfmqBDpHBTFl4RZ+yL5IUbmJyGCtq8MSbk5aWIQQohaLVeHTDNvaZH+6uT9DUiJQqVSSrLSxfol6esSGoChw/5Jdrg5HeABJWIQQopaMU0XkFFcSGuDHjWlS3Kw9De8aCUDmmWIKy4xNHC18nSQsQghRy8YjFwC4vk8sITrpNW9Pj43r4bj/n91nXRiJ8ASSsAghfMKR/FLue28n3/6Y3+hx208UAnBNz5iOCMunJegDCbSvKVRYbnJxNMLdScIihPAJf117mPWHLzD7/QwKGuh+qDRZ2He2BLjUXSHaT0llNZX2Wixmi1esEiPakSQsQgif8GNuqeP+86sOXPGYnaeKMFsVEvQBJEVI2fj2dij3Ug2W7rHBLoxEeAJJWIQQXu9CqZHsogrH4y/25bL2QF69476zdxdd1ztGZgV1gD4Jlxa6S4mUhEU0ThIWIYTX+8uaQwB0jgzi4Wu7A/DMyv2UVFY7jlEUxbFu0Lg+cR0fpA/SB/o77ocH+TdypBCSsAghfMDes8UA/GJsd349viddo4PJNxhZsPpHxzH7zpZwrqSKIK2G0T2jXRSp70mOtHW9Gc2yrpBonCQsQgivVmY0cyS/DICByREE+GtYcOtVACzdeYatxwsAWLEnB4BxfWIJsM9cEe0vWGubOl5mlIRFNE4SFiGE1zpZUE76n78FbGvYdLIPpB3eLYq7h3cGYM5/s6gwmfkqKxeAWwd3ck2wPupQnm0wdJBWkkTROElYhBBea8UPZyk1mgF4aEy3OoXg/jC5Dwn6AE4XVvDA+xmcLzUSpNUwqod0B7mCViMfR6Jx8hsihPBafvYPwZ8OSeL/JvWpsy80wJ8Xb+kPwNbjtmJxo3tGo/OTb/quEBumc3UIws1JwiKE8Fp5hiqg7myU2sb1ieMnAxIdj6+X2UEdrmb2uJ9aPo5E4+Q3RAjhlcwWK5uP2tYFGtZI1drnbkolOkRHkFbDdX2kHH9HsloVFHuBWz+11L0RjZOVvYQQXmnV3nOcKaokIsifkY2MS4kK0bH68dGYLFZiQwM6MEJhtl4qx6+WhEU0QRIWIYRX+nKfbdbPrJFdmlx1OSZUxk+4gqVWwiItLKIp0iUkhPA6iqKw61QRIONS3JlFuZSwaCRhEU2QhEUI4XXyDFUYqsxo1Cp6xYe4OhxxBYqiUFV9qVicJCyiKdIlJITwOofsKzN3iw6Wacpu6mf/2sG2E7bp5FqNWrqERJOkhUUI4XUO59sSltqrAQv3seT7k45kBWBGeoqsji2aJC0sQgivY7CvwhwpKwC7nS1HC5j3xUEA0pL0/Hp8T67tFeviqIQnkIRFCOF1okNss34yz5a4OBJRm9Fs4enPs1AUuGNoEi/dliYtK6LZpEtICOF1usUEA1BcYXJxJKK2r7JyOVVYQUyojmempkqyIpwiCYsQwuucLqwAoGdsqIsjEbVtPloA2FpXQgOku044R7qEhBBeo9xo5r4lu9h50laDJSUqyMURidqy7YlkaoLexZEITyQtLEIIr/He9ycdyQrA4M4RLoxGXK7SXnclSCdTzYXzpIVFCOE1th6/NFV2xaMjGSQJi1sxW2yVba21SvIL0VySsAghvEJVtYWMUxcB+OpXo0lNlBos7uTHXIOjPk7NGCMhnCEJixDCK2w+WoDJYiVBH0DfBBls6y4O55Xy6jdHWHMgD7CV4O8VJ++PcJ4kLEIIr7DW/oE4qX+8TJd1E2sP5PHwR7up6QGampbAExN60T1G1ncSzpOERQjhFfafMwAwsnu0iyMRAIfyDPz6k0ysClzVSc+fb7mKq5JkdpBoOUlYhBDtrtJkIVDbfjNDLFaF4xfKAOgVJ9/eXa2o3MQD72dQYbIwsnsU798/DH+NTEoVrSO/QUKIdrVq7zlSn1vDE59kUmEyt8trnCwox2S2EuivISlCaq+42lvrj3H2YiWdI4N46+7BkqyINiG/RUKIdvXJrmwUBVbsyeGWN7dysqC8zV/jx1xbd1CfhFA0ahm/4mo/5tnej4ev7U54kNbF0QhvIQmLEKLdGM0W9tVagPBwfik/eWML3xzMb9PX2ZNdDEDfBJnK7GqKovBjrm36cj+ZWi7akCQsQoh2c95gpLTK1g20bc44hqZEUGo08+AHGTz9eRalVdVt8jpr9ucCMEAGdbpcnqGKonITahX0jpfpy6LtSMIihGg3P2RfdNyPDQ1g6UMjuHdkFwA+2p7Nwx/txmi2tOo1zhRVcK6kCo1axbg+ca06l2i9FXtyANvCkwH+UoJftB1JWIQQ7eZUga2iaY/YEDRqFf4aNc//pB/v3juUIK2G748V8tH27Fa9xpdZttaVq7tEEBOqa3XMouUqTRbe+PYYAD8dmuTiaIS3kYRFCNFu8gxVAIzrE1tn+7g+cfx+Ym8APss4g6K0bG0ZRVH4z+6zANw8sFMrIhVt4XRROZXVFnR+au4f1dXV4Qgv41TCsmjRItLS0ggLCyMsLIz09HRWr17t2F9WVsZjjz1GUlISgYGB9O3bl0WLFjV6ziVLlqBSqerdqqqqWnZFQgi3UWa0jV8JukINllsGJaHzU3Mor7RO15EzcoorOXbeVn9lUv/4lgcq2kTNAOsByeGoZbaWaGNOFY5LSkpiwYIF9OjRA4D333+fadOmsWfPHvr168cTTzzB+vXr+eijj+jSpQtr167l0UcfJTExkWnTpjV43rCwMA4fPlxnW0BAQAsuRwjhTkIDbH9i8krqfwHRB/lzQ794/rf3HBuPFDAkJdLp8/9gnx3Uv1OYTJ91A1uOFgAwWFbJFu3AqRaWm266iRtvvJFevXrRq1cvXnzxRUJCQti+fTsA27ZtY9asWVx33XV06dKFhx56iAEDBpCRkdHoeVUqFfHx8XVuQgjPpigKH++wjU/ZcbLoisdc0yMKgC1HL7ToNfbn2L7RD0qWD0hXq6q2sP7QeQAmpMY2cbQQzmvxGBaLxcKyZcsoLy8nPT0dgGuuuYZVq1aRk5ODoiisX7+eI0eOMHHixEbPVVZWRkpKCklJSUydOpU9e/Y0+fpGoxGDwVDnJoRwH1k5l+qvjOl55fV9rukZA8DesyUYWjDF+XShrQhdQri0yLrahsMXKDWaiQ8LkARStAunE5asrCxCQkLQ6XQ8/PDDrFixgtTUVAAWLlxIamoqSUlJaLVaJk2axFtvvcU111zT4Pn69OnDkiVLWLVqFUuXLiUgIIBRo0Zx9OjRRuOYP38+er3ecUtOTnb2UoQQ7egPy7Mc939jH2B7uU7hgXSNDsZiVdh+vNDp16ipaquV0u8ut2yXrTXtpgEJMn5FtAun/5f37t2bzMxMtm/fziOPPMKsWbM4ePAgYEtYtm/fzqpVq9i9ezd//etfefTRR1m3bl2D5xsxYgT33HMPAwYMYPTo0Xz66af06tWLN954o9E45syZQ0lJieN25swZZy9FCNGOcoorAfjnjCGEBfg3eNw1PWytL98fK3Dq/MUVJjYctnUl9YiVBQ9dyWyxOt6/24bIdGbRPpxerVmr1ToG3Q4dOpRdu3bx+uuv89prrzF37lxWrFjBlClTAEhLSyMzM5NXXnmF8ePHN+v8arWaq6++uskWFp1Oh04nNReEcFcllbYuntiwxrtrRvWI5sPtp9nsZMLyWcZZKkwWOoUHMsbetSRcI7uogmqLQoC/ml6xUt1WtI9Wt6MqioLRaKS6uprq6mrU6rqn1Gg0WK1Wp86XmZlJQkJCa0MTQrhI7VWZ9YENt64ApHePQq2CExfKOWdvlWnK+dIqXllrm1n4wOiu0gXhYkftU8t7xIbIeyHajVMtLHPnzmXy5MkkJydTWlrKsmXL2LBhA2vWrCEsLIxrr72W3/3udwQGBpKSksLGjRv54IMP+Nvf/uY4x8yZM+nUqRPz588HYN68eYwYMYKePXtiMBhYuHAhmZmZvPnmm217pUKIDqPz05AcGciZokqyckroGh3c4LH6QH/SksLJPFPMV1m5PDC6W5Pnf3vjCYxmK12jg5mZ3qUNIxctkW8vEJgUHuTiSIQ3cyphyc/PZ8aMGeTm5qLX60lLS2PNmjVMmDABgGXLljFnzhzuvvtuioqKSElJ4cUXX+Thhx92nCM7O7tOK0xxcTEPPfQQeXl56PV6Bg0axKZNmxg2bFgbXaIQoqNp1CquTonkTFEO2faZPI0Z3zeWzDPF/OnLH9l3toSnp/YlNvTKXUkXy00s3nISgOTIIMfAW+E6FSbbelDBOqdHGQjRbE79di1evLjR/fHx8bz33nuNHrNhw4Y6j1999VVeffVVZ8IQQngAs9VWbt/SjB7hB0Z340KpkQ+2n2bV3nOsP3Se307szT0jUuolJMt/OOu4f/+oLm0ZsmihikYqGgvRVmQuoBCiXWj9bH9emjPjOMBfw7xp/Vn1i2tIS9JTajTz3KoD3Pzm9+w9U+w47nRhOQu/tQ3InzO5D9f1lgJl7qDc3sIiCYtoT5KwCCHanKIo7D5tWx8oIrj5JfOvStKz4tFRvDCtH6EBfmTllHDzW9/z9OdZlFRW8/q6oxiqbN/mZ43s0h6hixaw2hevbNkSlkI0j3Q4CiHa3IbDFzhZUE6Av5pJ/ZxbakOjVjEjvQsT+8cz/6tDrNiTw0fbs/loe7bjmAHJ4QT4y7d5d5GoDwTg7MUKF0civJm0sAgh2twX+3IBmD40maiQltVLig0N4NXpA/n4weF0j6k7y+iXY3u0OkbRdlITwwDYn+P8EiklFdUUV5jaOiThhaSFRQjRpswWK2sP5gEw0cnWlSsZ2T2a1Y+PYdXec5gtVn46NFlmBrmZ/ol6wFZArqSiGn1Q47V3auw4Ucis93YS4K9hzeNjiNfLmlCiYdLCIoRoU/tySiitMqMP9Gd4t6g2OafWT83tQ5K4c1hnSVbckD7Inwh7kpJnr8nSHH/75ghV1VaKK6pZtOFYe4UnvIQkLEKINrXlqK3E/qgeUZJc+JB4+ziW082ouwNwKM/AjpNFjsefZJyhqFy6hkTDJGERQrSpmmnIveJkTRlf0jfe9n7vPVvc4DF7si/y9sbj/PF/B5m5eCcAU65KICUqiKpqKyv25HREqMJDScIihGgzuSWVmOyV4sqN5iaOFt5kTC/bApSf7DpD9RWqBeaWVHLnP7czf/Uh3v3+JOdLjWj91Pzy+h70jbcN2q2qtnRozMKzyKBbIUSbWH/4PA+8n4HFXuG2p6za61OmpCXwwhcHKSgz8cPpi/XGL72/9TRGsxWVCu4Ykky11crNAzvRJz7M0XUYLIXnRCMkYRFCtIllO7MdyUpSRCBT0mTFdV/ir1HTOz6UrccLybGvum0yW/n+eAFZZ0v4YNspAP5xz5B6s8dqfm80zSmLLHyWJCxCiDZRU9n252O68fC13WUhPB/UMzaErccLWbThOGaLwtubjnP8wqVBuMO6RDK+b1yDz7c0Z+Ep4bPkL4oQotX+uvYwBWUmtBo1D4zu5lQ5fuE9Hr6uO//bl8vR82X8fvk+wNbNM7ZPLOndo7htcNIVZ45VmW1jV6otUtxfNEwSFiFEq+QUV/LWhuMAPHJdd2JCW1bZVni+BH0gH80ezlsbjpFdVMHVXSL51fU90Qc2XEjOZLaSccrWOjeijer2CO8kCYsQolU+2HYKi1UhvVsUT0zo5epwhIulJobx958Nbvbxe88WU2afUdbPXuJfiCuREU5CiFbZePgCALcNSXJxJMITZRdeWjDRaJYxLKJhkrAIIVolKcJW4XT94fMujkR4ouv7xjruv/v9SRdGItydJCxCiFYZkhIJwI4TRSiKDJoUzgkP0vLiLf0BW9E5+R0SDZGERQjRKveN6gJAQZmxzhRWIZrrlkGdCNJqyC6q4JGPfnDUZRGiNklYhBCt4q9RExpgG79/5mJFE0cLUV+Q1o97R3YBYM2BPN7fesql8Qj3JAmLEKLFFEXh5je/p7TKjFajpk+8lOMXLfPkhF5MtVdHfmfzCazSyiIuI9OahRAt9vTn+8nKKQHgT7f0J0Ef6OKIhKfy06h56bY0vtiXy7mSKjJOX2RY18i2f6Hn9Zfuh3Vq+/N7s8hucPd/wD/AJS8vCYsQokW2nyjk3zuyAegdF8odQ5NdHJHwdME6PwYkh7P3TDHHL5S1T8JSmyGnfc/vbQw5kL8fkoa65OUlYRFCOM1ssfLsyv2Ox5/+PN2F0QhvUlMV9woV/NtGSByU5UP6Y3DV7e30Il5o6c+g9By4cBaXJCxCCKct3ZnNkfwydH5qNv/fWPRBDZdeF8IZhspqAEztta5Q53Q4+DmEd4bEQe3zGt7Iz/Xrg8mgWyGEU0oqqvnrN0cAmHtjX2JDXdOfLbxTTXn+g+cM7fMCgRG2fysvts/5RbuRhEUI4ZQR87+luKKaBH0Adw/v7OpwhJeZkBoHwNcH8jhd2A51fYLs42Iqitr+3KJdScIihGi2o/mlVFZbAPjjtP74aeRPiGhb6d2j6BIVRFG5iXF/3cjf1h5u2xeQFhaPJX9thBDNUlJRzV3/2g7AsK6Rjm/CQrQlnZ+GZQ+lM7J7FBarwsLvjrHjRGHbvUCgvYWlUlpYPI0kLEKIZvkkI5uCMhMA/zept4ujEd4sXh/Axw+OYLp9qvzcFVlU2Vv2Wq2mhUW6hDyOzBISQjRLhcn2gTEgSe9Y8FCI9jTnxj58e+g8xy+UM/aVDTx3Uyo9YkPYcPgCVkUhSOvH9X1jnStYWDOGRbqEPI4kLEKIZrlYbmtd6Rod7OJIhK8ID9Ly8k/TuO+9XeSWVPHwRz/UO+bpzyFBH0CvuFD6JIQyolsUw7tGEqRt4OPNMYZFWlg8jSQsQohmCfDXAHCgvaabCnEFY3vHsuup8Ty/6gBfH8jDoiiM7B5FXGgAJwvL2ZNdTG5JFbklVWw8coG3N55Aq1EzsHM4I7tH8ch13dH5aS6dsGYMS1UJWC2g1lz5hYXbkYRFCNEsW4/bBj7eNUymMouOFROq4827B1NaVY0ChAVcKlRoqKrmaH4ph/PK2He2mM1HC8gprmTnySJ2nizih+xiPrh/2KWTBYZful9ZDMFRHXUZopUkYRFCNGn7iULHIodT7CvqCtHRQgPqV1QOC/BnSEokQ1Ii+dnwziiKwvELZYz/2yYANh25UPcJGn/QhYHRYBvHIgmLx5BZQkKIJi1YfQiA6BAdcWFS2Va4L5VKRY/YUBbPsi3Q1yc+tP5BNa0sMo7Fo0jCIoRoksa+Et19o7q4NhAhmql7TAgApwsr6u8MlJlCnkgSFiFEk+L1tlaVr7JyXRyJEM0TFWJbrK+y2kKZ0Vx3p5Tn90iSsAghmjQgSQ/YZgidN1S5OBohmhai86NTuK0+y4o9OXV3Snl+jyQJixCiSYH2mhYpUUFEh+hcHI0QTVOpVDwwuisAf1lziKyzJZd2Snl+jyQJixCiUSazlX9sOA7ArPQuqO3jWYRwdzNGpDCsSySlVWZmvLuDo/mlth3SwuKRJGERQjRqzYE8cooriQrW8rPhUoNFeA4/jZp377uagcnhFFdUM/PdnRSUGWUMi4eShEUI0agtR211LG7oF++odiuEpwjR+bHkvqtJ0AeQW1LF1wfypDy/h5KERQjRqE1HCgDo3ynMxZEI0TLhQVrG9IwBILuwQqY1eyhJWIQQDbJaFfLss4J62OtaCOGJRvWMBmDV3nOYtPbku0ISFk8iCYsQokEnCsoACPTXMKhzhIujEaLlbkiNIzZUR25JFd+fs9o2SguLR5G1hIQQDTqab0tYusUEo/WT7zfCcwX4axjeLYr/7T3H2Sr78hKmUjCbwE/r2uA6WFG5icN5pZQbzVRbrJgsVvw1asb2jiVQ677j1Jz6C7Ro0SLS0tIICwsjLCyM9PR0Vq9e7dhfVlbGY489RlJSEoGBgfTt25dFixY1ed7ly5eTmpqKTqcjNTWVFStWOH8lQog298U+W2Xb1AQZvyI8X5B90PimbBMK9un5VcWuC6idWa0KpwvLWZ2Vy1/XHub+JbsY8edvGfzCN9z1r+088EEGj/z7Bx5flsmj//6B97aedHXIjXKqhSUpKYkFCxbQo0cPAN5//32mTZvGnj176NevH0888QTr16/no48+okuXLqxdu5ZHH32UxMREpk2bdsVzbtu2jenTp/PCCy9wyy23sGLFCu644w62bNnC8OHDW3+FQogWsVoVvrSX4r9zWLKLoxGi9W5MS+Cz3Wf45lAhJbogwlXlKBWFqEJiXR1aqxnNFo7ml3HwnIGDuQbHv/WWJbDrHBlERLAWf7WKjNO2rrHkiKCODNlpKkVRlNacIDIykpdffpnZs2fTv39/pk+fzjPPPOPYP2TIEG688UZeeOGFKz5/+vTpGAyGOi01kyZNIiIigqVLlzY7DoPBgF6vp6SkhLAw+TYoRGttPVbAz97ZgUat4tALk/DXSJeQ8HybjlzgiU8y+U/1L+iqzufAxE/olz7J1WE5paSimgO5JXWSk2PnyzBb63+cazVqesWH0C9BT2piGKmJYfSJDyU0wB+A3acvctuirQRrNWQ8PaHhLqHXB8DFUzB7HSRf3abX09zP7xaPYbFYLHz22WeUl5eTnp4OwDXXXMOqVau4//77SUxMZMOGDRw5coTXX3+9wfNs27aNJ554os62iRMn8tprrzX6+kajEaPR6HhsMBhaeilCiCvYcMRWf2XKVQmSrAivMaZXDBlPj+f4/Agw5bM+87DbJyyKovDh9tNsOVrAgXMGcoorr3icPtCf1IQw+tkTk9TEMLrHhDT6/3dVpm2dpYn94t16/Aq0IGHJysoiPT2dqqoqQkJCWLFiBampqQAsXLiQBx98kKSkJPz8/FCr1bzzzjtcc801DZ4vLy+PuLi4Otvi4uLIy8trNI758+czb948Z8MXQjTDueJKPt6RDcCk/vEujkaItqVSqUiIT4TsQ5w+e5aTBeV0jQ52dVgNWrX3HM+uPFBnW1JEoC0xqdVykqgPQKVq/tIZFqvCl1m2z9qbBiS2acztwemEpXfv3mRmZlJcXMzy5cuZNWsWGzduJDU1lYULF7J9+3ZWrVpFSkoKmzZt4tFHHyUhIYHx48c3eM7Lf8CKojT5Q58zZw5PPvmk47HBYCA5WfrZhWgLf19/jDKjmV5xIdyQGtf0E4TwMMHhMZAN4ZTx1vpjvPzTAa4O6YoUReHxZZkARAZrefNng0lNDEMf6N/qc+84UUhBmZHwIH9G9Yhu9fnam9MJi1ardQy6HTp0KLt27eL111/ntddeY+7cuaxYsYIpU6YAkJaWRmZmJq+88kqDCUt8fHy91pTz58/Xa3W5nE6nQ6eTVWOFaGv7c0pYttPWuvL8T/rhJ91BwhvZy/OHq8r41+6z/HRoMsO6Rro4qPp+zC113L9/VBfSu0e12bn/Z58FOKlfvEeULWh1hIqiYDQaqa6uprq6GrW67ik1Gg1Wq7XB56enp/PNN9/U2bZ27VpGjhzZ2tCEEE6yWhWeWbkfqwI/GZDIyO7u/61LiBaxl+cfap8g9OAHGazae45WzkNpM4qiYLUqbDtR6Nh26+CkNjt/tcXK6v22hGVqmvt3B4GTLSxz585l8uTJJCcnU1payrJly9iwYQNr1qwhLCyMa6+9lt/97ncEBgaSkpLCxo0b+eCDD/jb3/7mOMfMmTPp1KkT8+fPB+Dxxx9nzJgxvPTSS0ybNo2VK1eybt06tmzZ0rZXKoRo0icZZ9iTXUywVsNTU/q6Ohwh2o+9hWVQtJV+hHHgnIFfLd3De9+f5Pmb+jEgOdzpU353KJ+F3x5zTCX216gZ3jWSyf3jGdolEo266fElhqpqPtx2mve+P0WFyUyFyQLAXcOSSQwPdDqmhnx/rIDiimqigrWM6OZ+LUtX4lTCkp+fz4wZM8jNzUWv15OWlsaaNWuYMGECAMuWLWPOnDncfffdFBUVkZKSwosvvsjDDz/sOEd2dnadVpiRI0eybNkynn76aZ555hm6d+/OJ598IjVYhOhgJy6U8cIXBwH49fhexIUFuDgiIdpRkO1DWmsqYcWjo3hrwzEWbTjOnuxi7vzndt6eMYQxvWKadSqT2cpf1hzinS31C6/9mGtgydZTdI8J5stfjW5wxXOj2cKb3x3jva2nKK2qXztF28ZdszVFIW+8KsFjun2dSlgWL17c6P74+Hjee++9Ro/ZsGFDvW233347t99+uzOhCCHa2PzVh6gwWUjvFsX913R1dThCtK/AcNu/lRfR+qn59fhe/Gx4Z3772T42HbnA7Pd3sfDOQUy+KqHR02QXVvDLpT+w92wJAPeO7MKk/vEoCpRUVvPNwXyW/3CW4xfKuVBqJDnyysXZ5n91iCVbTwHQIzaER6/rTrDOjz/+7yB5hirS27B71mi28PUB29jRqWmNX587kbWEhBBkF1aw7sd8AF64uV+zmq6F8Gj2MSy1F0CMDQ3gnZlDeeKTTL7MyuWxpXt4U6VqcGr/d4fyeXxpJqVGM/pAf1756QAmXDarbkS3SJb/cNZ2/rArTxTZn1PCB9tOAfCX29K4fUgSavv/wWt7xVBpshAR3HbrHW06UkBplZm4MB1Xd/GM7iCQ1ZqF8HmKojDrvZ0oiq2oVo/YUFeHJET7s49hoaKozmatn5qFdw3itsFJWKwKjy/bw57suqs6K4rCO5tPMPv9DEqNZoakRPDV46PrJSsAeYYqACKC/NH5XeoOMlusVJoslFRU89SKLKyKrRbKHVcnO5IVsC3a2JbJCsAX+84Btu4gtQd9OZEWFiF83NqD+ZwsKAfgAekKEr7CPoYFcyVUV4L/pQGtGrWKv9yexsUKE98dOs+DH2Sw4tFRJEcGYTJbefrzLD7NsLWa3DUsmXk/6d/gtOB8g60iu8lsZea7OzlbVMHZ4kpM5rqzZ0N1fjzTAQPdTWYr6w7aWlM9oVhcbdLCIoSP+/mHuwGY3D++2YMMhfB4ujBQ2Vs8Ki/W261Rq1h41yD6JoRRUGbiwQ8yOG+o4p7FO/g04yxqFTw7NZU/33JVozVMKu2zfMpNFjYducCJgvJ6yYpWo+aZm1KJ7YCB7plniik3WYgK1jKoBTOhXElaWITwUYqiOGYKAPxibA8XRiNEB1OpbN1CFQW2hCWsfmtDiM6Pd+8dypSFWziUV8qwP38L2FpDFv5sEGN7N73K85he0Tx+fU8sVoXkyECSI4JIiggiLNAPf43aflM5VVK/NbYeLwAgvXtUh71mW5GERQgf9cW+XH65dI/jcd8EWeVc+JigSFvCctk4ltoS9IE8cm13XvzqRwA6RwaxeNZQesY1b6xXkNaPJyb0apNw28L3xy4lLJ5GEhYhfJDZYmXOf7Mcj7fPuV5mBgnfUzPw9gpdQrXNHJnC2oN5RARpWXBbGpFtPAi2o5QZzezJLgZgTE/P6/6VhEUIH/TV/jxHNc7lj6QTr5ciccIHOaY2N9zCAqDz0/DZw56/XMzWYwWYrQopUUEN1oNxZzLoVggf9PGO0wA8OLorQ1I8pw6DEG2qmS0s3uLLLNuYtXF9mh57444kYRHCx+QUV7L9hO0bpSxuKHxazdTmRsaweIsKk5m1B2zTmacN7OTiaFpGEhYhfMzR/EvL1Y/uKQmL8GGO8vzen7B8czCfymoLKVFBDEjSuzqcFpGERQgfs/yHHAA6hQd6zKJnQrQLxxiWYpeG0d7MFiv/2HgCgJ8MSPS46cw15K+VED4ku7CCL+1luRfcdpWLoxHCxRooz+/JzhVX8vyqA6y1L24I8PamE/yYa0Af6M+9I7u4LrhWkllCQviQ1ftzsSowrGskoz1wWqMQbSqo/gKInu6lNYdYmXmOJVtPMfuarmj91Ly98TgAT03pS1TIlRdg9ASSsAjhI0oqq3lz/TEAplzlOUvKC9FuHLOEvKOFpaSimtX7L7WsLN5y0nF/+tBkfjokyRVhtRlJWITwEZ/vycFQZaZnbAj3jEhxdThCuF5grRYWRbGV6/dgq/adw2S20ic+lF+O68nq/bmYLQoT+8cxbUAnjx27UkMSFiF8xIFzJQD0jg+VqrZCwKUWFosJTOWgC3FtPK30WcYZAH46NJkpaQlMSfOullQZdCuEjygqrwZsawhVW6xNHC2ED9AGg8ZeZt/Dx7H8mGtg39kS/NQqbh5YfyFHbyAJixA+YN/ZYtb9mO94bKisdmE0QrgJlarZ5fnd3WcZZwEY3zfOowfWNkYSFiF8wMtfH3bcv39UV6/9gyaE07ykPP+a/bay+7d7+MDaxsgYFiG8XIXJzOajtiXlfzWuB0/e0NvFEQnhRrygPH++oYpzJVWoVZDePcrV4bQbaWERwsudLqxw3L9bZgcJUZcXtLDsyS4GoFdcKME6722HkIRFCC9XWGYCoEtUEHFhAS6ORgg34wW1WDLPFAMwqHO4S+Nob5KwCOHlArUaAE4VVlBcYXJxNEK4GUd5fs9sYVEUhe8O2QbUD+oc4eJo2pckLEJ4OW2tBQ4rqy0ujEQIN+Th5fkP5ho4kl+Gzk/NxH7xrg6nXUnCIoSXe2uDrRz/DalxJOgDXRyNEG7Gw7uEttgH1I/uGY0+0N/F0bQvSViE8GJ7zxQ71hZ5YkIvF0cjhBsK9OwWlu0nCgEY0c17ZwfVkIRFCC+lKApPfJoJwM0DE+mbEObagIRwR44xLJ7XwqIoCvvO2pbcGJLi3eNXQBIWIbyWyWLlZEE5AI+Pl9YVIa7Ig8ew5BmqKCw3oVGrfOILiSQsQngpnZ+G7jG2xdxO2RMXIcRlatdhURTXxuKk/TkGAHrGhhDgr3FxNO1PEhYhvNhVnfQAZOWUuDgSIdxUzRgWxQJGg2tjcdJ++//rfol6F0fSMSRhEcKL9bcnLDX93EKIy/gHgH+Q7b6HjWM5er4UgNRE7+8OAklYhPBqNQPxNh+9wPELZS6ORgg35aHl+S+UGgGIC/ONxUwlYRHCiw1I0jM0JQKj2cpP3tjiWNFVCFGLY2qz57SwWKwKR/JtX0I6Rwa5OJqOIQmLEF5MpVLx5t2DGdYlknKThV8u3cMOe90GIYRdYLjt38piV0bhlE1HLlBSWU1EkL9PzBACSViE8HpxYQF8/OBwRveMptqi8M9NJ1wdkhDupWZqsweNYfnWvn7Q1LRE/DW+8VHuG1cphI/z06iJCtYCeH35biGc5oHl+XOLqwDfGXALkrAI4RN+zDXwxT7b+JVZI7u4Nhgh3I0HlufPM9gSFl8ZcAuSsAjh9YorTPxy6R7MVoUJqXEMSA53dUhCuBcPLM9fbjQDoFH7zse471ypED6opLKaGYt3cux8GXFhOhbcepWrQxLC/Xhgef7B9pIFW48VuDiSjiMJixBeqsxo5t73dpKVU0JksJYPZw8nKsR3mo+FaDYPHMOSbl+d2ZeqWPu5OgAhRNsrrarm3vd2sSe7GH2gPx/NHk6vuFBXhyWEe/LAMSxRIbZB9GX2riFfIC0sQnihuSv2s/v0RcIC/Phw9jCfmkkghNM8cAyLyWxbqNFXpjSDJCxCeLUbr0ogLSnc1WEI4d5qxrBUlYDV4tpYmulCma0sf2iA73SUSMIiXK7aYsVq9axl3d3dtb1iAPhyXy4W+dkK0biaFhYUW9LiATKzi4FLK7L7AklYhEuVVFQz9E/r6Db3K5Z8f9LV4XiNlZk5AJQazdz61vccyS91cURCuDGNP2jtY7w8YBxLpcnC2oN5AAzvGuXiaDqOUwnLokWLSEtLIywsjLCwMNLT01m9erVjv0qluuLt5ZdfbvCcS5YsueJzqqqqWn5VwmP88YuDlFRWA/D8/w7yY67BxRF5B6tyqVVl79kS3pNkUIjGBXnOOJZ/7zhNaZWZpIhARnaXhOWKkpKSWLBgARkZGWRkZDBu3DimTZvGgQMHAMjNza1ze/fdd1GpVNx2222NnjcsLKzecwMCAlp+VcIjbDteyPIfztbZ9qule1wUjXd5bfogeteaFTRQisUJ0TjH1Gb3bmFRFIV/78gG4JHruqNWq1wcUcdxarTOTTfdVOfxiy++yKJFi9i+fTv9+vUjPj6+zv6VK1cyduxYunXr1uh5VSpVvecK71ZpsjDnv/sAuGdEZz7abvsPePR8GbkllSToA10ZnseLCdXxz5lDuPblDahUcH3fOFeHJIR7c0xtdu8WlqPnyzhZUI5Wo+YnAxJdHU6HavEYFovFwrJlyygvLyc9Pb3e/vz8fL788ktmz57d5LnKyspISUkhKSmJqVOnsmdP09+yjUYjBoOhzk14jtfWHeFUYQUJ+gB+PqZ7nX2yOF/rlVRW89jHtv9Hw7pEEi0F44RonIe0sHy93zZ2ZVSPKEIDfOtvpdMJS1ZWFiEhIeh0Oh5++GFWrFhBampqvePef/99QkNDufXWWxs9X58+fViyZAmrVq1i6dKlBAQEMGrUKI4ePdro8+bPn49er3fckpOTnb0U4SL7zhbzr80nAHjxlv6M/st6x75tc8YRpPWdaXptTVEUPt+Tw9Q3Njsq3L54i5TjF6JJNVOb3XwMy9f2wbYT+/ler4TTCUvv3r3JzMxk+/btPPLII8yaNYuDBw/WO+7dd9/l7rvvbnIsyogRI7jnnnsYMGAAo0eP5tNPP6VXr1688cYbjT5vzpw5lJSUOG5nzpxx9lKEC1RbrPz+P/uwKjC6ZzT3L8lw7EvvFiVdQU04VVDO7CW72JN95W+Br35zhF9/ksmZokoS9AF8NHs4PWJDOjhKITyQB5TnzymuZH+OAZUKxqf6Xjev019ltVotPXr0AGDo0KHs2rWL119/nbfffttxzObNmzl8+DCffPKJ0wGp1WquvvrqJltYdDodOp00c3uatzce51BeKZHBWq7pEc3mo7aFuyakxvHXOwa4ODr3dbqwnDn/zWLr8UIANhy5wLEXJ6NSXRpwV1JRzcLvjgGQqA9g3W+uldYqIZrLA8rzf/tjPgBDUyJ8spu31XVYFEXBaDTW2bZ48WKGDBnCgAHOfwApikJmZiYJCQmtDU24mWPnS1n4re0D9bmbUqmpZza8ayT/mjmUMB/rj22u3JJKfvavHY5kBcBiVeoselZuNHPvkp0ARAVrWf7oSElWhHCGB5TnzzxTDMCoHtGuDcRFnEpY5s6dy+bNmzl16hRZWVk89dRTbNiwgbvvvttxjMFg4LPPPuOBBx644jlmzpzJnDlzHI/nzZvH119/zYkTJ8jMzGT27NlkZmby8MMPt/CShDuyWBV+/599mCxWxvWJ5ScDEukaHQzAjpNFbD9R2MQZfFNVtYVxr2wkp7iSpIhAltx3NZP72/qu/7f3nOOYBz/IcCx0+O8Hh0vXmhDOCnL/FpZDubYCkKkJvrk2mFNfwfLz85kxYwa5ubno9XrS0tJYs2YNEyZMcByzbNkyFEXhrrvuuuI5srOzUasv5UnFxcU89NBD5OXlodfrGTRoEJs2bWLYsGEtvCThjj7cdoofsosJ0fnxp5v7o1KpSK9V8OjOf27n7RlDfHIgWWP+/t0xKqst+GtUfPzACDpHBXE0v4zV+/PIKa4E4NmV+9l6vJBgrYb37x9Gn3jf/GMmRKt4wBiWAvv6QYnhvvmFxKmEZfHixU0e89BDD/HQQw81uH/Dhg11Hr/66qu8+uqrzoQhPMzZixX85evDAPxhch/HfzZ9oD8v3tKfp1bsB+DnH+6WpKWW97ee4u/rbV1of5jcl85RQQCcK7ElKkkRQazYc5ZPM86iUsHbM4ZKgTghWsoxhqXYpWE0pKra4ljwMC7MNwurylpCol0pisLcFfupMFkY1jWSnw3rXGf/3cNTWP7IpTo+i7d4Zwn5MqOZBasP8fWBvGYt9PjprjM8t8pWQfrB0V25f1QXx76asT7/3HSC331mK773q3E9uaanb/ZrC9EmarqEjAawVLs2lis4caEcRbF90YsO0bo6HJeQhEW0q//+kMOmIxfQ+qlZcOtVVywjPSQlklnpKQCcuFDW0SF2iFe+Psw/Nh7n5x/u5sEPMlCUhpOWo/ml/PELW6mA3nGhzL2xb53ZQJP6x+OvsT02WxUm9YvnV9f3bN8LEMLbBegB+/8zN2xlKa4wARAXpqvz98CXSMIi2s2FUqPjg/eJ8b3oFtNwPZCkCFt3R2G5iUqTpUPi60hHz19aLfnbQ+dZuvPKdYOOnS/lrn/toMxopnNkEF89PrreH6e+CWHMmdwXgCEpEfxt+gA0PrSeiBDtQq2xJy245TiW00UVAD5X3bY2SVhEu3n+fwcoqaymf6cwHhzdtdFjbx7UCQBFgW0nCjoivA5VbrQlYTUzo1744qBj0GyNM0UV3PPOTgrKjKQmhLHyF6MaTETuv6YrO+dez2c/T5fpy0K0FTcuz7/aXpJ/XJ9YF0fiOpKwiHbx9YE8vtyXi0at4qXb0vDTNP6rFqjVOO739rJZLsUVJvadLQbg/fuG0TkyiMpqC1MWbuacPWk5WVDObYu2kmeookdsCP9+YDgRwY33U8eGBfjUSq1CtDs3Lc9/qqCc74/ZvsjVlDXwRZKwiDZXUlnNM5/bZ/6M6Ua/RH2Tzzljb+4MD/Knk5dN2dtw+AJWxTYepXNUEHcOs617VVxRzStfH2br8QLGvrKB86VGuscE8+HsYU0mK0KIduCmLSyfZpzBYlUY0yum0a51bydtyaLNzf/qR86XGukWHdzswaC59qm6AX6aJo70PDUVadOSbInbo9f1wGJR+Os3R/jvnhz+uycHAK1GzdKHRhAb6ptTFoVwOcfUZvdpYbFaFVZm2opETh/q24v8SguLaFNbjxWwbJdtQOmC29II8G9eAmKoNANQWuV+0wlb6+outj+C6w+fx2S2AvDIdd2pPZZ2RLdIvnlyjCQrQriSG5bnz8opIae4kiCthuv7+u74FZCERbShSpOFP/w3C4AZI1IY1jWy2c8d1DkcgHKTxdE95C2u7xtLdIiOgjKTY/EyP42ax8b2IDpEx+t3DmTpgyNIiQp2caRC+Dg3LM9fbbF9ydEH+jf7C6C3koRFtJm/fXOY7KIKEvUB/H5Sb6eeW/vDesHqQ20dmkv5a9T8dGgSAEt3XZrO/JsberPrqeuZNrCTz9ZVEMKtuGF5fp29m9zaSO0mXyEJi2gTe88UO6rUvnjLVS2qFTDY3sryZVYu2YUd08qiKArlRnO7v85o++qqm49ecKwHAkiiIoQ7CXS/FpaCctvfi6hgnYsjcT1JWESrmcxW/m/5PqwK3DwwkbEtrBOw9KERjvtjXl5PXklVW4XYoFfWHqbfc1/z0fbT7fYaJrOVZ+1l9juFBxKk9e1mXSHclmMMi/skLCcvlAO2Cre+ThIW0Wr/2HicQ3mlRAZrefamfi0+j85Pw59vucrx+PZ/bG2L8BqkKAorfrDN0Hn68/3t1tLywbZTHDtfRnSIls8elkJvQritIPeb1vzdofMAjOwua4VJwiJa5Wh+KW98dxSA53/Sj8hW1g+5bUgnEvW2mTJnL1ayJ7v9/nB0nfMV52q14rz3fdsvvHi6sJzX19l+Pr+9oTcJeu+qMSOEV3Gzac1f7svl++O2gnG+PkMIJGERrWCxKvx++T6qLQrX94nlprSEVp9T56dh65zrHY9/9599rT7nlRw8Z6i37e1NJyipaP206pqFDfMNVcxYvJNSo5nBncP5qY/XUBDC7dV0CVVXQHX7d0k35uzFCp74NBNFgVnpKT5dMK6GJCyixd7feoo92cWE6Pz40y3923QAaU2BpGPn22f15q8P2NblUKlg/7yJ9IoLobTKzL82n2jR+axWhW9/zGfcKxvoOucrFm85ydQ3tpBdVEF8WABv3j1YFigUwt0F6EFlH2Pm4m6hd7ecwmS2MqxLZKu62r2JJCyiRSpNFv669jAAc27s0+ZdHVMHXGqtKTeaMVRVO1ou2sJnGbbpxbPSuxCi8+PJCbZp2O9+f7LZg30VReFIfin/2Hic8X/byOz3MzhRYBsg98IXB7lQaqRXXAif/HyEdAUJ4QlUKggMt913YcJSUlnNJ7uyAXh0bHf5smMno/+E084bqhj2528B26yXu67u3OavMTA53HG/33NfO+7/+4HhjOwe1arWHItVcYxdmWLvxprYL45BncPZk13M3BVZLJ41tMHXMFusfLwzmw+2na7TAhQa4EdplW3grloFU9MS+fOtVxGik/9mQniMwEioKHTpOJZPdmVTbrLQKy6Ea3vFuCwOdyN/SYXTXvv2qOP+Q2O6tcuKwaEB/kzqF88ae9dNjbvf2cFVnfSsemxUi5KWD7ad4tmVBxyPBySFA7Z6KC/dlsbUhVv47tB5/vtDDrcNSar3/IxTRTz9+X4O5ZUCtvV/RvaI4vo+sdw6OIkgrYYfc0uJCdUREyrTEIXwOC5eAFFRFJZ8fwqAB67pJrWaapGERTSbxaqwZn8e/9t7zrFt1sgu7fZ6/5gxhPWHzrMy0zb1+HP7AmBZOSXszzFwVVLTq0DXtjort06y0ic+FK3fpV7RXnGhPD6+Jy9/fZh5/zvANT2jiQuzzViqtlh5duV+lu60dSXpA/15YnxPbh2SRNhlRfJSE8Ocv1ghhHuoKc/vovWECstNjhbgyVfFuyQGdyUJi2iWHScKeW7VAUfLQtfoYFY8OrLdX3dsn1hHIbrfTuzNNS+tB2DV3pxmJyxf7svlFx//UGfbXcOSeXpKar1jfz6mG2sP5LH3bAlz/mvrGjJbFR77+Ae+PmBbB+jOq5P5/aQ+rZ7CLYRwQy4uz7/1eCEA3WKCW1Qx3JtJwiIate14IY99/AOF5SbHtp8N78xTN/YluIPHZiRFBDH3xj78+atD/JBd3OznXZ6s7Jx7PbFhV14V2U+j5pWfDmCKvWto+Q857D1TzNcH8tH6qXn7niEtruQrhPAALi7PXzODcWI/aV25nCQsokEbj1xg1rs7HY/vGtaZ39zQi+gQ143NqJlts/v0Rd7acIxHr+vR6PGXzyx6e8aQBpOVGj3jQvn1hJ78Zc1h/rB8H2argkoFb9w1SJIVIbydozy/a1pY9py2JUo164+JSyRhEfWUGc1c/9cN5BsuLdL3xl2DuGlAogujsuleq3jSy18fZsaIlEabTT/YdmmNoIN/nNjssvgPje7G1/ttXUMAz9/UT77xCOELXFyeP04fwLmSKoorW1/E0ttIHRZRh9WqcOtb3zuSlelDkzkwb6JbJCtgG9D64i39AVAUeGrF/gaPfeGLgzxnX3RwTK8Yp9bw8dOoef3OQUzqF88bdw1q18HFQgg34uJZQgF+tsJ1Fmvb1Z3yFtLCIhwMVdWMmv8dpfZFAGdf05VnptYfmOpqdw9PwarAM5/vZ9Xec0QE+TNvWv86xxzKM7B4i21toOFdI3njrkFOv06X6GD+MWNIm8QshPAQLh7DUmW2AOCvkenMl5OERQB1i8EBPD2lLw+M7ubCiBo3Y0QKz3xua115f9tpTBaFC6VGLpRWcaHUWGdRw2UPjZBaBkKI5nHhtGaT2cqhXNtMzC7RwR3++u5OEhZBVbWFn769zfF4fN84Zl/T1YURNc+6J8cw/m+bAFi6M/uKxzRWsVYIIeqp3SWkKLZy/R1k79liKqstRAVr6R0X2mGv6ykkYfFx1RYrv/lsL6cLKwDbLBpPGVzaIzaUf9wzmC3HCogOsVWWjQ0NICZUR4I+gNhQnSQrQgjn1HQJWYy2VZu1HdfSsds+Q2h4t0j523UFkrD4uFe+PsyX+3LxU6tYct8wrunpWVPpJvVPYFL/hKYPFEKI5tAGg9ofrNW2VpYOTFhqFl5NjgjqsNf0JDJLyIet2Z/L25tOAPD6nYM8LlkRQog2p1K5ZByLoihsOHwegH6dnFt2xFdIwuKjLpab+L/lWQDcN6qLY9ViIYTweS6Y2pxx+iKnCisI0mq4XgpUXpF0CfmgY+dLHYNVe8eF8tSNfV0ckRBCuBHH1OaOa2H5dJdtYdWpaQkdvuyJp5AWFh9jqKp2JCsAz96Uip9Gfg2EEMKhg8vzlxvNfJmVC8BPhyZ3yGt6Ivmk8iH7c0pIe36t4/GS+65mlKxXIYQQdXVwef7PM3OoMFnoGh3M0JSIDnlNTyQJi4/Yffoid7+zw/F47o19uK639JMKIUQ9HTiGpcxo5tVvjgJw9/DOMp25EdJR5gPOG6q4772dGKrM9IkP5ZWfDqC/jEIXQogr68Dy/O9uOUlBmZEuUUHMTO/S7q/nySRh8QEbj1zAUGUmNMCPZQ+NIDxI6+qQhBDCfXXQGJb3vj/J3745AsCj1/VA6yedHo2Rn44PCAv0B6BbTIgkK0II0ZSg9m9hsVgVFm04DsC9I7tw+5CkdnstbyEJiw+IsCcpJRUmF0cihBAeoAOmNW86eoHzpUbCAvyYc2Mf1GoZu9IUSVh8QLXFCiD/IYQQojnaedCt2WLl5TWHAbh9SDI6P027vI63kYTFB9QUITpVUE5JZbWLoxFCCDdXu0tIUdr01Iqi8KtleziYayBU58dj43q06fm9mSQsPuD4+TIArAqESAVFIYRoXE0Li9UMxtI2PXXG6Yt8lZWHSgV/uT2NyGAZV9hckrD4gJpp/SO7R6GRbiEhhGicfyD4Bdrut/E4ltfW2WYFTR+azOSrZA03Z0jC4gOyiyoAKK0yuzgSIYTwEO0wjuVccSXfHytEo1bxi7HSFeQsSVi83PELZby2zlZFUQooCiFEM9WMY2nDWiwnC8oB6BIVRHJkUJud11dIwuLlXrUXJQK4a1hnF0YihBAepB1aWE4V1iQswW12Tl/iVMKyaNEi0tLSCAsLIywsjPT0dFavXu3Yr1Kprnh7+eWXGz3v8uXLSU1NRafTkZqayooVK1p2NaKOr7Jy+WKfbQXQkd2jJGERQojmaoeE5XShrXs+RRKWFnEqYUlKSmLBggVkZGSQkZHBuHHjmDZtGgcOHAAgNze3zu3dd99FpVJx2223NXjObdu2MX36dGbMmMHevXuZMWMGd9xxBzt27GjwOaJxFSYzq/ae49F//+DY9vC13V0YkRBCeJh2KM9/yt4llBIl3UEtoVKU1k0yj4yM5OWXX2b27Nn19t18882Ulpby7bffNvj86dOnYzAY6rTUTJo0iYiICJYuXdrsOAwGA3q9npKSEsLCwpy7CC/yyteH+fv6Y3W2bf79WOkvFUIIZ6x7Hra8Cr1vhEEz2uSUz606QE5xJY9f35OrPG0B2v89DuXnYfY6SL66TU/d3M/vFhflsFgsfPbZZ5SXl5Oenl5vf35+Pl9++SXvv/9+o+fZtm0bTzzxRJ1tEydO5LXXXmv0eUajEaPR6HhsMBiaH7wX+2DbqTqPX5s+UJIVIYRwVlCU7d/DX9lubWAegBbY3Cancw2164a+Op2wZGVlkZ6eTlVVFSEhIaxYsYLU1NR6x73//vuEhoZy6623Nnq+vLw84uLi6myLi4sjLy+v0efNnz+fefPmORu+V3t3y0kM9qnL/3vsGrrFBDuq3AohhHBC6s1wclObjWExWazszykBVAxMDscjS2JFdof4AS57eac/zXr37k1mZibFxcUsX76cWbNmsXHjxnpJy7vvvsvdd99NQEBAk+dUXTbfVlGUetsuN2fOHJ588knHY4PBQHJyshNX4l0+2HaKP35xEIDBncO5KsnDmhuFEMKdhCfD3Z+12el2Hy/krn9tJyUqiI0Pjm2z8/oSpxMWrVZLjx62gjdDhw5l165dvP7667z99tuOYzZv3szhw4f55JNPmjxffHx8vdaU8+fP12t1uZxOp0On0zkbvtd6f+spx/3Fs9q2f1EIIUTryJTm1mt1Z5SiKHXGkgAsXryYIUOGMGBA001H6enpfPPNN3W2rV27lpEjR7Y2NJ9SZrR1Bf3jnsFEyNoUQgjhVmpmCHWNloSlpZxqYZk7dy6TJ08mOTmZ0tJSli1bxoYNG1izZo3jGIPBwGeffcZf//rXK55j5syZdOrUifnz5wPw+OOPM2bMGF566SWmTZvGypUrWbduHVu2bGnFZfmeLlHB5BuM/GvzSSb1l/UphBDCnZyUhKXVnEpY8vPzmTFjBrm5uej1etLS0lizZg0TJkxwHLNs2TIUReGuu+664jmys7NR1xplPHLkSJYtW8bTTz/NM888Q/fu3fnkk08YPnx4Cy/JN6Ul6dlxsojdp9uuyJEQQoi24SjLLwlLi7W6Dou78PU6LG+uP8bLXx9maloCf//ZYFeHI4QQws5qVejz7BpMZiubfjeWzlI4ro7mfn7LWkJeIso+bqWwzOTiSIQQQtSmYEtaAPw0njif2T1IwuIldp6ylY/uFRfi4kiEEELUplGrSAi3lfg4e7HSxdF4LklYvEBRuYkv7Ysc/mRgooujEUIIcbnkCFs30NmLFS6OxHNJwuIF8kqqMJqtAHSNlhYWIYRwN0kRgYC0sLSGJCxeILuo3HG/oMzYyJFCCCFcIcnewnKmSFpYWkoSFg+3P6eEOf/NAmBUjyh6xYW6OCIhhBCXS46UFpbWkpXxPJSiKKzen8ej//4BAJ2fmnk/6e/iqIQQQlxJTQvL2WJpYWkpSVg8jNWqkHm2mF8vyyTb3rQYrNXwn0dG0iNWxq8IIYQ7qhnDkltchdlixU8jHRzOkoTFjZVUVPOnLw9y9HwZSRGB6Pw07Mm+yAl7xUQ/tYqfX9uNh8Z0Rx/o7+JohRBCNCQ2NAB/jYpqi0KeocrR4iKaTxIWN/bfPWf5bPdZADLPFNfZ1yc+lJduS2NAcnjHByaEEMIpGrWKTuGBnCqs4OzFSklYWkASFjdlsSrM/+pQve06PzXf/fY6EvUBqFRSMVEIITxFUkSQI2ERzpOExU29svYwJosVjVrFP2cMYVyfWDYcvkCniEA6hQe6OjwhhBBOqhnHIlObW0YSFje18fAFAH4xtgfX940DYGyfWFeGJIQQohWkeFzryDBlN2WoqgZgaEqEiyMRQgjRFpIjpTx/a0jC4oZKKqrJKbZl4PH6ABdHI4QQoi1IC0vrSMLihv637xyKYpsJJJVrhRDCO9TMDMotqaTaYnVxNJ5HEhY3c6aogqc/3w/AbYOTXByNEEKIthITokPrp8aq2BatFc6RhMXNfLj9tOP+bUMkYRFCCG+hVqtICpeZQi0lCYubqSmtEh7kT2Sw1rXBCCGEaFOdZBxLi0nC4mb2nSkBoG98mIsjEUII0dYciyDKTCGnScLiZrpEBwNgURQXRyKEEKKtJUdKC0tLSeE4N1BSWc2mIxf4+kAeX+zLBcBolhHkQgjhbWpaWM5IC4vTJGFxIatV4Z0tJ3h93VHKTZY6+25KS3BRVEIIIdqL1GJpOUlYXGT94fPM/+pHjuSXARAZrKWo3ESwVsM/Zgzhmh7RLo5QCCFEW0uxV7vNM1RRbjQTrJOP4eaSn1QH23myiNfWHWHr8ULHtt9N7M3D13ZHo5bVl4UQwptFheiIDdVxvtTIobxShsjyK80mCUsHOVNUwZ+/+pHV+/MA8FOrmDWyC49c153oEJ2LoxNCCNFRUhPDOH/4AvtzSiRhcYIkLO1MURReW3eURRuPY7IPpJ2QGseTE3rRN0GmLgshhK8Z3DmCDYcvsOtUEbNGdnF1OB5DEpZ2VFhm5K5/bXeMUxneNZJ50/rRR2qsCCGEzxrWNRKwDRFQFAWVSoYDNIckLO3EYlWYsXinI1m5a1gyf77lKvnFFEIIHzcwORx/jYrzpUayiypIiQp2dUgeQQrHtZKiKOw8WcSKPWcpLDMCUGY08/yqAxzMNQDw5s8GM//WNElWhBBCEOCvIS0pHICMUxddG4wHkRaWVigsM/Kzf+3gcH4pAFo/NXFhOs4UXZpf/9r0gUyRmipCCCFqSUvSs/v0RQ6cM3DbEFdH4xkkYWmhi+UmHl+W6UhWAExmqyNZ6RYdzOPjezJtYCdXhSiEEMJN9U/UA7D/XImLI/EckrC0wOajF3jog91UVltQq+BfM4cytncspwrLOXOxkgR9AD1iQlBLXRUhhBBX0K+TbfLFwXMGrFZFPi+aQRIWJ5QZzTy9IovPM88BEBrgx5L7rmZIim3Ed7eYELrFhLgyRCGEEB6gR0wIOj81ZUYz2UUVjoVvRcNk0G0znSmq4PGlexzJCsDCOwc5khUhhBCiufw0avrYa3Fl5Ui3UHNIC0sznCuuZPRf1jsev3Bzf2aMSHFhRN5JURTOFFWiVttG0Qf4awjwU+OnkbxaCOF9BiTp2XummD3Zxdw0INHV4bg9SViaYeG3Rx33HxrTjXuGd3ZhNN5rwepDvL3pRL3t/hoVOj8NWj81Wo0afz8VWo0arZ8GrUaF1k9NgL+GB0d3Y0yvGBdELoQQzqupdn6ioMzFkXgGSViasO5gPst2nQHgtzf0YkJqPKcKK/DX2D40/TVq/DQqFECxglVR7Ddbi4FVubRNUWwF5ayKQmJ4IAH+GtdenJv5an8uAFqNGpPF6thebVGotpjB2Pjzw4O0krAIITxGzcrN2YUVLo7EM0jC0oSPd2Y77r+y9givrD3SJucN1fnRNzEMjUqFSgXqWv+qVaC67N+a/bbHtba14LWtioLZqmCxKlRbFCxWqyOxUhRQULBaLz12JFyAotjOoVKBCls8Ksdj28baj20xX7pPvefYHju6g1Sw+5nxBGv9MJqtVFVbqDJbqKq2Um2xYjJbMdn/rbZY2X36Iq+ts7WA3StrcgghPEjnKFvCcuZiBRargkZmCjVKEpYmPDauB6EBfuSWVJFbUkmF0eL4wDRZrI4P8CtRq0CjVtVJOtQqFUazhVKjmZ0nizruQjzEwORwQgP8AQjUagjUNt4K9Y+Nxx33H/ogg8TwQDpHBpEcGUTnWreE8AD8ZSyMEMKNJOgD8deoqLYo5JZUkhQR5OqQ3JokLE0Y3DmCwZ0bXv7bbLFitiq1WkcutYw09pytxwsprTLX6S66vGVDoXaXkq2LSbnssVVRcLadRaUCP7UKjUZt+1etQqNSoVZfagmpey2XWnZUYG9pqd3iUhMvjrgvPbZldHW2K3XPgX2fChWje0U7dS1+6ktJSGG5icJyU4Mj7iODtUSHaIkO0RETqiM6REdksJYAf82ln4P9Z6FRqwgL9Ccy2J/wIC0RQVr0gf7yDUgI0WY0ahXJEUGcKCgnu7BCEpYmSMLSSn4aNX5ODkXx06hlrEUbWXLf1VwoNWI0WymtMpNTXEl2UQVniirItt/OFFVgNFspKjdRVG5yLEjpLJUKwgL8iQiqSWL8iQjSEh6kJTE8gK7RwYQHadH5qQnR+RERpCU0wE8KQgkhGtQ5ypawnC6qYKSrg3FzkrAIj6ZSqYgNC3A8Tk0Mq3eM1apQVGGioMxIQant3wulRgrKjFysMFFVbcViH9Njtg+KrrZYMVSZKSo3UlxeTanRjKJASWU1JZXV0MxBcmoV6ANrEht/gnV+GKutVFZbqKy2OM7np1YRHaJztABF21uAYuyPo2r2heoI1fnJQppCeInONQNvi2TgbVMkYRFeT+1IBnQQ37JzVFusFFdUU1xh4mJFNRcrTJful5scrTmlVWaqqi2UGc1UmCxYFezHVzd6fhM4ztEUnZ+6bnIToiM6tNb9EB0xoVqignWEB/lLcuODrLWS7yuNs2vqV+Ly/Zd3O9ffX3diQG1V1RZOXCjHZLHSNyEUP7W6yW5zsBXrfGnNIQxVZkfXMlDnemper/Yg/kv7Lj1S1Tqey7bW3nal42pfe0MhX+lnbO/wrnecozvc3r1/yv7lR2YKNU0SFiGawV+jJibUNvaluYxmCyX2ZKUmwakwWexF8Wy1Y8IC/NEH+mOxKrYWoDIjF8pMFNhbgGy3mtYhI+UmC0azlZziSnKKK5sOAhzjclT2QeCOWWaO7So06lrjltTYxjSpVKjVdQeMa9SXnqtWXeG89v21z1uz79JYKRV+ahV+GhV+anWd2WiX/zG31ox5su+z1hkTVd/lHzhX+gBTXX4wlz6Urvy8Kx9T977tjtlixWiuO5ut9qy2mn+rLQpGsxWz9VLrnsVqu+7Lf/41P7+Cskvz+mNCdZeSEvu/FuXSfVdzzHyEBuO50qzImutWqcBQZe7YoF1Mvlc0TRIWIdqJzk9DbJimTpdVY5qzlkilyXLFRKbm8YWafaVGxx98i1XBcsWPd+GWLE0fcqG0iaJELqYoYKnV7BAW4IeiQKnRXO8Y2+U2/PvZJz6Uh8Z0q5M4qlRcSnJrJbv1A6l991Kye/krXtpW95g6x9Uky1B/msNl2caVEt4aNYlc7RYpf42K63rHXukKRC1OJSyLFi1i0aJFnDp1CoB+/frx7LPPMnnyZMcxP/74I//3f//Hxo0bsVqt9OvXj08//ZTOna9cHXbJkiXcd9999bZXVlYSENC8P/RC+IpArYZk+7TtphjNFgyVl2ai1XyDryleWNOC4Xhsn6FmURQURcFSUwjRaj+u5jnWS89T7MdbFezba72O/X7Ntkv3bS0R1fbWAVWtb9gqLrXgAHVnqlG3y6GmG6DG5R9EtbsR6h9Tv4tBuexx7eOu2OSv1P8A9LMXlNT5qW2Vmf3UaDUaW6FJe6Xmmu3+GjX+GluLgp9abZulp1LV+TnWzBK0WBXKjWYO5ZWi81PTL1GPn+O59lYYe8uVozVLfalF7PJrrX29l1/PlffVfnDZvstmBVovmxGo81MTHuSPVYGyWjMjaxfVrP37c6kmlIK/Rk1KlCwKKGycSliSkpJYsGABPXr0AOD9999n2rRp7Nmzh379+nH8+HGuueYaZs+ezbx589Dr9fz4449NJh5hYWEcPny4zjZJVoRoHZ2fhphQqabsTYZ28dzFVjUq0Af5uzoM4cFUypW+hjghMjKSl19+mdmzZ3PnnXfi7+/Phx9+2OznL1myhF//+tcUFxe3JgwMBgN6vZ6SkhLCwurPFBFCCCGE+2nu53eLS39aLBaWLVtGeXk56enpWK1WvvzyS3r16sXEiROJjY1l+PDhfP75502eq6ysjJSUFJKSkpg6dSp79uxp8jlGoxGDwVDnJoQQQgjv5HTCkpWVRUhICDqdjocffpgVK1aQmprK+fPnKSsrY8GCBUyaNIm1a9dyyy23cOutt7Jx48YGz9enTx+WLFnCqlWrWLp0KQEBAYwaNYqjR482+ByA+fPno9frHbfk5GRnL0UIIYQQHsLpLiGTyUR2djbFxcUsX76cd955h40bNxIeHk6nTp246667+Pjjjx3H/+QnPyE4OJilS5c26/xWq5XBgwczZswYFi5c2OBxRqMRo/HSSHmDwUBycrJ0CQkhhBAepLldQk5Pa9ZqtY5Bt0OHDmXXrl28/vrrvPHGG/j5+ZGamlrn+L59+7Jly5Zmn1+tVnP11Vc32cKi0+nQ6ZpfE0MIIYQQnqvVy9cqioLRaESr1XL11VfXm+1z5MgRUlJSnDpfZmYmCQkJrQ1NCCGEEF7CqRaWuXPnMnnyZJKTkyktLWXZsmVs2LCBNWvWAPC73/2O6dOnM2bMGMaOHcuaNWv43//+x4YNGxznmDlzJp06dWL+/PkAzJs3jxEjRtCzZ08MBgMLFy4kMzOTN998s+2uUgghhBAezamEJT8/nxkzZpCbm4teryctLY01a9YwYcIEAG655Rb+8Y9/MH/+fH71q1/Ru3dvli9fzjXXXOM4R3Z2Nmr1pYad4uJiHnroIfLy8tDr9QwaNIhNmzYxbNiwNrpEIYQQQni6VtdhcRdSh0UIIYTwPO1eh0UIIYQQoqNIwiKEEEIItycJixBCCCHcniQsQgghhHB7TheOc1c1Y4dlTSEhhBDCc9R8bjc1B8hrEpbS0lIAWVNICCGE8EClpaXo9foG93vNtGar1cq5c+cIDQ1FpVIBl9YXOnPmjEx1dkPy/rg3eX/cm7w/7k3en+ZTFIXS0lISExPr1Gm7nNe0sKjVapKSkq64LywsTH5h3Ji8P+5N3h/3Ju+Pe5P3p3kaa1mpIYNuhRBCCOH2JGERQgghhNvz6oRFp9Px3HPPodPpXB2KuAJ5f9ybvD/uTd4f9ybvT9vzmkG3QgghhPBeXt3CIoQQQgjvIAmLEEIIIdyeJCxCCCGEcHuSsAghhBDC7XltwnLkyBGmTZtGdHQ0YWFhjBo1ivXr11/x2MLCQpKSklCpVBQXF3dsoD6qqfdn79693HXXXSQnJxMYGEjfvn15/fXXXRixb2nO/5/s7GxuuukmgoODiY6O5le/+hUmk8lFEfuODRs2oFKprnjbtWuX47hdu3Zx/fXXEx4eTkREBDfccAOZmZmuC9xHNPf9AViyZAlpaWkEBAQQHx/PY4895qKoPYPXJixTpkzBbDbz3XffsXv3bgYOHMjUqVPJy8urd+zs2bNJS0tzQZS+q6n3Z/fu3cTExPDRRx9x4MABnnrqKebMmcPf//53F0fuG5p6fywWC1OmTKG8vJwtW7awbNkyli9fzm9+8xsXR+79Ro4cSW5ubp3bAw88QJcuXRg6dChgW5Nl4sSJdO7cmR07drBlyxbCwsKYOHEi1dXVLr4C79ac9wfgb3/7G0899RR/+MMfOHDgAN9++y0TJ050YeQeQPFCFy5cUABl06ZNjm0Gg0EBlHXr1tU59q233lKuvfZa5dtvv1UA5eLFix0cre9x5v2p7dFHH1XGjh3bESH6tOa8P1999ZWiVquVnJwcxzFLly5VdDqdUlJS0uEx+zKTyaTExsYqf/zjHx3bdu3apQBKdna2Y9u+ffsUQDl27JgrwvRZV3p/ioqKlMDAwEb/3on6vLKFJSoqir59+/LBBx9QXl6O2Wzm7bffJi4ujiFDhjiOO3jwIH/84x/54IMPGl1wSbSt5r4/lyspKSEyMrIDI/VNzXl/tm3bRv/+/UlMTHQ8b+LEiRiNRnbv3u2q0H3SqlWrKCgo4N5773Vs6927N9HR0SxevBiTyURlZSWLFy+mX79+pKSkuC5YH3Sl9+ebb77BarWSk5ND3759SUpK4o477uDMmTOuC9QTuDpjai9nz55VhgwZoqhUKkWj0SiJiYnKnj17HPurqqqUtLQ05cMPP1QURVHWr18vLSwdqKn353Jbt25V/P39lbVr13ZckD6sqffnwQcfVCZMmFDveVqtVvn44487MFIxefJkZfLkyfW279+/X+nevbuiVqsVtVqt9OnTRzl9+rQLIvRtV3p/5s+fr/j7+yu9e/dW1qxZo2zbtk25/vrrld69eytGo9FFkbo/j2pWeP755xsczFRzy8jIQFEUHn30UWJjY9m8eTM7d+5k2rRpTJ06ldzcXADmzJlD3759ueeee1x8Vd6jLd+f2g4cOMC0adN49tlnmTBhgguuzDu09fujUqnqvYaiKFfcLprW3PentrNnz/L1118ze/bsOtsrKyu5//77GTVqFNu3b+f777+nX79+3HjjjVRWVnbkZXmNtnx/rFYr1dXVLFy4kIkTJzJixAiWLl3K0aNHG5wcIjysNH9BQQEFBQWNHtOlSxe+//57brjhBi5evFhnWe+ePXsye/Zs/vCHPzBw4ECysrIcf1wVRcFqtaLRaHjqqaeYN29eu16LN2rL96fGwYMHGTt2LA888AAvvvhiu8XuC9ry/Xn22WdZuXIle/fudey/ePEikZGRfPfdd4wdO7bdrsNbNff9CQgIcDx+4YUXeOONN8jJycHf39+xffHixcydO5fc3FxHd7fJZCIiIoLFixdz5513ts9FeLG2fH/ee+897r//fs6cOUNSUpJje1xcHH/605948MEH2/4CvICfqwNwRnR0NNHR0U0eV1FRAVBvXIparcZqtQKwfPnyOt80du3axf3338/mzZvp3r17G0btO9ry/QFby8q4ceOYNWuWJCttoC3fn/T0dF588UVyc3NJSEgAYO3ateh0ukbHIYmGNff9qaEoCu+99x4zZ86s82EItvdQrVbXae2qeVz7/5hovrZ8f0aNGgXA4cOHHQlLUVERBQUFMsaoMS7rjGpHFy5cUKKiopRbb71VyczMVA4fPqz89re/Vfz9/ZXMzMwrPkfGsHSc5rw/+/fvV2JiYpS7775byc3NddzOnz/v4ui9X3PeH7PZrPTv31+5/vrrlR9++EFZt26dkpSUpDz22GMujt53rFu3TgGUgwcP1tv3448/KjqdTnnkkUeUgwcPKvv371fuueceRa/XK+fOnXNBtL6nsfdHURRl2rRpSr9+/ZTvv/9eycrKUqZOnaqkpqYqJpOpgyP1HF6ZsCiKbVrfDTfcoERGRiqhoaHKiBEjlK+++qrB4yVh6VhNvT/PPfecAtS7paSkuC5oH9Kc/z+nT59WpkyZogQGBiqRkZHKY489plRVVbkoYt9z1113KSNHjmxw/9q1a5VRo0Yper1eiYiIUMaNG6ds27atAyP0bU29PyUlJcr999+vhIeHK5GRkcott9xSZxq6qM+jxrAIIYQQwjd51CwhIYQQQvgmSViEEEII4fYkYRFCCCGE25OERQghhBBuTxIWIYQQQrg9SViEEEII4fYkYRFCCCGE25OERQghhBBuTxIWIYQQQrg9SViEEEII4fYkYRFCCCGE25OERQghhBBu7/8BI7Be3+ld/vMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now, repeat for another clipPoly\n",
    "\n",
    "plotPoly(tractMAP)\n",
    "pt1 = Point(-76.5,38.25)\n",
    "pt2 = Point(-76.3,37)\n",
    "pt3 = Point(-75,37)\n",
    "pt4 = Point(-75,38.25)\n",
    "clipPoly = Polygon([pt1,pt2,pt3,pt4])  #this is Assateague + S. Cheseapeake Bay\n",
    "plotPoly(clipPoly)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cac3531a-35c7-438d-b5b9-5fcdf0745329",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have flagged  38 tracts w pop 76784.0  to reassign to tracts...\n",
      "[10, 12, 13, 46, 47, 59, 69, 80, 81, 139, 167, 168, 169, 170, 171, 172, 173, 174, 175, 183, 185, 186, 189, 193, 208, 233, 252, 253, 256, 257, 259, 260, 386, 581, 760, 764, 765, 766, 883, 900, 901, 912, 913, 914, 915, 916, 948, 949, 950, 951, 952, 953, 956, 1023, 1024, 1025, 1026, 1095, 1108, 1109, 1110, 1122, 1125, 1132, 1337, 1340, 1343, 1344, 1346, 1347, 1350, 1351, 1354, 1359, 1360, 1361, 1373, 1374, 1375, 1387, 1388, 1500, 1543, 1545, 1782, 1844, 1845, 1847, 1850, 1851, 1852, 1855, 1856, 1882, 1886, 2023, 2024, 2154, 2157]\n",
      "I have flagged  49 precincts to reassign to precincts...\n",
      "[704, 707, 708, 712, 919, 1055, 1252, 1437, 1561, 1562, 1563, 1564, 1565, 1567, 1568, 1569, 1570, 1572, 1573, 1574, 1576, 1580, 1581, 1629, 1630, 1632, 1633, 1637, 1642, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1659, 1663, 1664, 1665, 1666, 1667, 1668, 1675, 1706, 1823, 1830, 1834, 1842, 1844, 1845, 1874, 1892, 1912, 1933, 2077, 2078, 2131, 2134, 2135, 2137, 2138, 2169, 2170, 2171, 2172, 2173, 2175, 2224, 2225, 2374, 2430, 2431, 2445, 2446]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#find all tracts and precincts centered in this clipPoly, flag for cutting\n",
    "# and, ID all nearby tracts and precincts to receive their pops and voters\n",
    "cutTractList = [-99999]\n",
    "cutPrecinctList = [-99999]\n",
    "tractReceivers = [-88888]\n",
    "precinctReceivers = [-88888]\n",
    "popToCut = 0.\n",
    "for t in range(nTracts):\n",
    "    x = tractGeom[t].centroid.x\n",
    "    y = tractGeom[t].centroid.y\n",
    "    if tractGeom[t].intersects(clipPoly) :\n",
    "        CP = Point(x,y)\n",
    "        if CP.intersects(clipPoly):\n",
    "            isSkippedTract[t] = 1\n",
    "            popToCut += tractPop[t]\n",
    "            if cutTractList == [-99999]:\n",
    "                cutTractList = [t]\n",
    "            else:\n",
    "                cutTractList.append(t)\n",
    "            plotPoly(tractGeom[t])\n",
    "    else:\n",
    "        if tractGeom[t].distance(clipPoly) < 0.1:\n",
    "            if tractReceivers == [-88888]:\n",
    "                tractReceivers = [t]\n",
    "            else:\n",
    "                tractReceivers.append(t)\n",
    "plotPoly(clipPoly)\n",
    "\n",
    "for p in range(nPrecincts):\n",
    "    x = vtdGeom[p].centroid.x\n",
    "    y = vtdGeom[p].centroid.y\n",
    "    if vtdGeom[p].intersects(clipPoly) :\n",
    "        isSkippedPrecinct[p] = 1\n",
    "        if cutPrecinctList == [-99999]:\n",
    "            cutPrecinctList = [p]\n",
    "        else:\n",
    "            cutPrecinctList.append(p)\n",
    "    else:\n",
    "        if vtdGeom[p].distance(clipPoly) < 0.1 :\n",
    "            if precinctReceivers == [-88888]:\n",
    "                precinctReceivers = [p]\n",
    "            else:\n",
    "                precinctReceivers.append(p)\n",
    "print(\"I have flagged \",len(cutTractList),\"tracts w pop\",popToCut,\" to reassign to tracts...\")\n",
    "print(tractReceivers)\n",
    "print(\"I have flagged \",len(cutPrecinctList),\"precincts to reassign to precincts...\")\n",
    "print(precinctReceivers)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d7009c9a-d5ff-4570-855d-1fb439afc32c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 2 of 4\n",
    "#visualize the to-be-cut precincts, just to confirm there are really xx precincts up there\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] ==1:\n",
    "        plotPoly(vtdGeom[p])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0218d8e6-7832-479f-b44f-b37c117ee40c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#clipPoly block 3 of 4\n",
    "#now visualize the receivers\n",
    "for pp in range(len(precinctReceivers)):\n",
    "    p = precinctReceivers[pp]\n",
    "    plotPoly(vtdGeom[p])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "5d698e51-7b2d-40b8-b932-d22f20f09bb0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#now visualize the TRACT receivers\n",
    "for tt in range(len(tractReceivers)):\n",
    "    t = tractReceivers[tt]\n",
    "    plotPoly(tractGeom[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c17c1582-29d1-41bc-8f56-b32ac70747ee",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have finished slicing  76784.0 people (VAP of 63210.0 ) and  78177.0 voters out.\n"
     ]
    }
   ],
   "source": [
    "#now, cut and redistribute\n",
    "cutPop = 0.\n",
    "cutVAP = 0.\n",
    "cutHisp = 0.\n",
    "cutBlack = 0.\n",
    "cutTrump = 0.\n",
    "cutBiden = 0.\n",
    "\n",
    "for ct in range(len(cutTractList)):\n",
    "    t = cutTractList[ct]\n",
    "    cutPop += tractPop[t]  #sum up the cut pops\n",
    "    cutVAP += tractVAP[t]\n",
    "    cutHisp += tractHisp[t]\n",
    "    cutBlack += tractBlack[t]\n",
    "    # Now we zero out the pops in the cut tracts\n",
    "    tractPop[t] = 0\n",
    "    tractVAP[t] = 0\n",
    "    tractHisp[t] = 0\n",
    "    tractBlack[t] = 0\n",
    "# Now distribute the pops among the receivers\n",
    "ntR = len(tractReceivers)\n",
    "NTR = float(ntR)\n",
    "for rt in range(ntR) :\n",
    "    t = tractReceivers[rt]\n",
    "    tractPop[t] += cutPop/NTR\n",
    "    tractVAP[t] += cutVAP/NTR\n",
    "    tractHisp[t] += cutHisp/NTR\n",
    "    tractBlack[t] += cutBlack/NTR\n",
    "\n",
    "#             now do the same for the precincts\n",
    "for cp in range(len(cutPrecinctList)):\n",
    "    p = cutPrecinctList[cp]\n",
    "    cutTrump += vtdTrump[p]\n",
    "    cutBiden += vtdBiden[p]\n",
    "        # Now we zero out the pops in the cut precincts\n",
    "    vtdTrump[p] = 0\n",
    "    vtdBiden[p] = 0\n",
    "\n",
    "# Now distribute the pops among the receivers\n",
    "npR = len(precinctReceivers)\n",
    "NPR = float(npR)\n",
    "for rp in range(npR) :\n",
    "    p = precinctReceivers[rp]\n",
    "    vtdTrump[p] += cutTrump/NPR\n",
    "    vtdBiden[p] += cutBiden/NPR\n",
    "print(\"I have finished slicing \",cutPop,\"people (VAP of\",cutVAP,\") and \",cutBiden+cutTrump,\"voters out.\" )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "84c2cf09-b3ea-4fc2-a55b-62985882836b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on tract 200\n",
      "working on tract 400\n",
      "working on tract 600\n",
      "working on tract 800\n",
      "working on tract 1000\n",
      "working on tract 1200\n",
      "working on tract 1400\n",
      "working on tract 1600\n",
      "working on tract 1800\n",
      "working on tract 2000\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#rebuild tractMAP, excluding skipped / sliced tracts.  #NOT NEEDED FOR OHIO -- NO SLICED populous TRACTS\n",
    "counter = -1 #Watchout - low-number tracts may have been skipped\n",
    "found = \"no\"\n",
    "while found == \"no\":\n",
    "    counter +=1\n",
    "    if isSkippedTract[counter]==0:\n",
    "        starter = counter\n",
    "        found = \"yes\"\n",
    "\n",
    "tractMAP = tractGeom[starter]\n",
    "for t in range(starter+1,nTracts):\n",
    "    if t%200 == 0:\n",
    "        print(\"working on tract\",t)\n",
    "    if isSkippedTract[t] == 0:\n",
    "        tractMAP = tractMAP.union(tractGeom[t])\n",
    "\n",
    "plotPoly(tractMAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "650cf37d-e11a-4ed3-861b-3f3edc411422",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#What is our distribution of precinct's Trump votes by precinct Biden votes after clipping?\n",
    "fig, ax = plt.subplots()\n",
    "ax.set(xlabel=\"Biden votes in this precinct\", ylabel=\"Trump precinct votes\")\n",
    "plt.plot(vtdBiden, vtdTrump, marker='.',linestyle=\"none\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d40408f3-31eb-4b8a-ad91-4e2eb5f422df",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#ALL TRIMS COMPLETE. let's convert the partisan data to the format we use for HD code\n",
    "# in this prototype, we only use 2020 presidential data, but this could be modified\n",
    "vtdGOP = [0.]*nPrecincts  #Each precinct's R/(R+D)\n",
    "vtdPop = [0.]*nPrecincts   #THIS IS VOTER POPULATION\n",
    "vtdArea = [0.]*nPrecincts\n",
    "vtdCPx = [0.]*nPrecincts   #these are centroid x and y of each precinct\n",
    "vtdCPy = [0.]*nPrecincts\n",
    "plotcolor = ['blue']*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    vtdPop[p] = vtdTrump[p] + vtdBiden[p] \n",
    "    vtdGOP[p] = vtdTrump[p]/max((vtdTrump[p] + vtdBiden[p]), 0.01)  #avoid divide by zero\n",
    "    if (vtdGOP[p] > 0.40) :\n",
    "        plotcolor[p]='purple'\n",
    "        if (vtdGOP[p] > 0.60) :\n",
    "            plotcolor[p] = 'red'\n",
    "    vtdArea[p] = vtdGeom[p].area\n",
    "    vtdCPx[p] = vtdGeom[p].centroid.x  #not needed except for graphing\n",
    "    vtdCPy[p] = vtdGeom[p].centroid.y   #not needed  \"  \"  \"\n",
    "    if isSkippedPrecinct[p] == 0 and p%10 == 0: #memory drain if we print all\n",
    "        plt.scatter(vtdCPx[p], vtdCPy[p], marker='.',c=plotcolor[p])\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a1e3f0d2-c21c-46d4-8227-e75dfd5e89b6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "original and final map areas are 11.290926653415056 9.42791080700504\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MAP = tractMAP  #committing to the trimmed map (for TN, using convex hull)\n",
    "#bufferDistance = 0.02  #do minor buffer for OH\n",
    "origMAP = wholeMAP    # let's keep a copy of the original map prior to buffering\n",
    "#MAPbuffer = MAP.exterior.buffer(bufferDistance, single_sided=True)  #gives a little exterior buffer\n",
    "# MAP = origMAP.convex_hull  #alternate to buffer for weird state shapes\n",
    "bBox = MAP.bounds\n",
    "MAPMinX = bBox[0]  #these four are useful for slicing ops, and are basis for map grid (without buffer)\n",
    "MAPMinY = bBox[1]\n",
    "MAPMaxX = bBox[2]\n",
    "MAPMaxY = bBox[3]\n",
    "\n",
    "#MAP = MAP.union(MAPbuffer)  #not buffering for TN\n",
    "print(\"original and final map areas are\",origMAP.area,MAP.area)  #same if we didn't buffer\n",
    "x2, y2 = MAP.exterior.xy\n",
    "plt.plot(x2,y2,c=\"green\")\n",
    "x2, y2 = origMAP.exterior.xy\n",
    "plt.plot(x2,y2,c=\"blue\")\n",
    "plt.show()\n",
    "\n",
    "minTractPop = 10  #was zero to not exclude empty interiors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8e271f55-e118-4575-bc99-c28c59f435b7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020 population, Trump+Biden voters, lean =  8631334 4375967 0.4484531300060009\n",
      "compare to Census 8631393 Leip has Trump + Biden = 4375998.0 0.4484531300060009\n"
     ]
    }
   ],
   "source": [
    "#let's confirm some population stats - these match 2020 census, USelectionatlas.org :-)\n",
    "censusPop = 8631393\n",
    "atlasTrump = 1962430.\n",
    "atlasBiden = 2413568.\n",
    "\n",
    "print(\"2020 population, Trump+Biden voters, lean = \",np.sum(tractPop),np.sum(vtdPop),stateGOP )\n",
    "print(\"compare to Census\",censusPop,\"Leip has Trump + Biden =\",atlasTrump+atlasBiden,\n",
    "      atlasTrump/(atlasTrump+atlasBiden) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6c47f717-f208-4a4c-b825-a3181a83c6ee",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "state pop before, after slice operation are 8631334 8631334.0\n",
      "state Trumpers before, after slice opn are 1962414 1962414.0\n",
      "state Bideners before, after slice opn are 2413553 2413553.0\n"
     ]
    }
   ],
   "source": [
    "#Check on integrity after slicing\n",
    "sumPop = 0.\n",
    "sumTrump = 0.\n",
    "sumBiden = 0.\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract[t] == 0:\n",
    "        sumPop += tractPop[t]\n",
    "for p in range(nPrecincts):\n",
    "    if isSkippedPrecinct[p] == 0:\n",
    "        sumTrump += vtdTrump[p]\n",
    "        sumBiden += vtdBiden[p]\n",
    "print(\"state pop before, after slice operation are\",np.sum(tractPop),sumPop)\n",
    "print(\"state Trumpers before, after slice opn are\",np.sum(vtdTrump),sumTrump)\n",
    "print(\"state Bideners before, after slice opn are\",np.sum(vtdBiden),sumBiden)\n",
    "for t in range(nTracts):\n",
    "    if isSkippedTract[t] ==1 and tractPop[t] > 0:  #should not occur\n",
    "        print(\"missed pop for tract, pop, (x,y)\",t,tractPop[t],tractGeom[t].centroid.x,\n",
    "              tractGeom[t].centroid.y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2f6c72cd-90d8-489d-9b15-d4278ba17b3d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "map has a total of 72 grids for 11 districts\n",
      "starting grid no 0 at x = -81.43249029166665, y = 36.784615333333335 \n",
      "starting grid no 5 at x = -81.43249029166665, y = 39.22224866666666 \n",
      "starting grid no 10 at x = -80.94249087499999, y = 38.73472199999999 \n",
      "starting grid no 15 at x = -80.45249145833333, y = 38.24719533333334 \n",
      "starting grid no 20 at x = -79.96249204166665, y = 37.75966866666667 \n",
      "starting grid no 25 at x = -79.472492625, y = 37.272142 \n",
      "starting grid no 30 at x = -78.98249320833332, y = 36.784615333333335 \n",
      "starting grid no 35 at x = -78.98249320833332, y = 39.22224866666666 \n",
      "starting grid no 40 at x = -78.49249379166666, y = 38.73472199999999 \n",
      "starting grid no 45 at x = -78.00249437499998, y = 38.24719533333334 \n",
      "starting grid no 50 at x = -77.51249495833332, y = 37.75966866666667 \n",
      "starting grid no 55 at x = -77.02249554166666, y = 37.272142 \n",
      "starting grid no 60 at x = -76.532496125, y = 36.784615333333335 \n",
      "starting grid no 65 at x = -76.532496125, y = 39.22224866666666 \n",
      "starting grid no 70 at x = -76.04249670833332, y = 38.734722 \n",
      "done building grids. avgGridDensity, maxGridDensity,nPopulatedGrids = 722626.6590749068 4721083.755018013 50.0\n"
     ]
    }
   ],
   "source": [
    "# this section - ESTIMATE POP'N DENSITY at scale of 1/3 of district length\n",
    "# also, IDENTIFY WHICH TRACTS and VTD's INTERSECT EACH GRID to speed later intersection searches by grid \n",
    "# (above sections already pulled in Tract and Precinct geometry and demographic data, built an overall map)\n",
    "nDistricts = 11   #VA congressional\n",
    "avgDistrictPop = np.sum(tractPop) / float(nDistricts)\n",
    "#MAPMaxX = -80.   #In most state maps, we figure this out from the bounding box of the convex hull; see above.\n",
    "#MAPMaxY = 31.1   # ... but for Florida, we will do manually\n",
    "#MAPMinX = -87.0\n",
    "#MAPMinY = 25.5\n",
    "stateWidth = float(MAPMaxX - MAPMinX)\n",
    "stateHeight = float(MAPMaxY - MAPMinY)\n",
    "stateWHRatio = stateWidth / stateHeight\n",
    "G = 2.5  #adjustable parameter; G*G = number of grids that fit in an average district\n",
    "nGridsX = int( G*round((nDistricts*stateWHRatio)**0.5,0) )   #OK to have empty grids for a non-rectglr state\n",
    "nGridsY = int(round(nGridsX / stateWHRatio,0) )  #so grids are square even if state has high aspect ratio\n",
    "nGrids = int(nGridsX*nGridsY)\n",
    "print(\"map has a total of {0} grids for {1} districts\".format(nGrids,nDistricts) )\n",
    "nGridPrecincts = [0]*nGrids # will store how many precincts intersect with each grid square\n",
    "nGridTracts = [0]*nGrids    # same, but for tracts\n",
    "gridPrecinctNo = [[0]*nPrecincts for gridNo in range(nGrids) ] # initialize a list of VTDs that intersect with each grid square\n",
    "gridTractNo = [[0]*nTracts for gridNo in range(nGrids) ] # initialize a list of tracts that intersect with each grid square\n",
    "\n",
    "gridPop = [0.]*nGrids #will store approx total population for this grid square\n",
    "gridDensity = [0.]*nGrids\n",
    "gridGeom = [Polygon([(0,0),(0,1),(1,0)])]*nGrids  #initialize grid geometry\n",
    "gridWidth = stateWidth /nGridsX        #geo length of a grid's side length\n",
    "gridHeight = stateHeight /nGridsY    \n",
    "\n",
    "for nG in range (nGrids) : #  create polygon shape for each grid square, compute grid-square population density\n",
    "    x = int(nG/nGridsY)\n",
    "    y = int(nG % nGridsY)\n",
    "    point1 = Point(x*gridWidth+MAPMinX,y*gridHeight+MAPMinY)\n",
    "    point2 = Point((x+1)*gridWidth+MAPMinX, y*gridHeight+MAPMinY)\n",
    "    point3 = Point((x+1)*gridWidth+MAPMinX, (y+1)*gridHeight+MAPMinY)\n",
    "    point4 = Point(x*gridWidth+MAPMinX, (y+1)*gridHeight+MAPMinY)\n",
    "    gridGeom[nG] = Polygon([point1, point2, point3, point4])\n",
    "    if (nG %5 == 0): #print occasionally, should take about one second per grid\n",
    "        print(\"starting grid no {0} at x = {1}, y = {2} \".format(nG,gridGeom[nG].centroid.x,gridGeom[nG].centroid.y) )\n",
    "    counter = 0\n",
    "    #    Now for each grid square, find intersxn with all polygons, total the intersection population\n",
    "    #    Also, create 2 lists: of TRACTS and precincts that intersect each grid (efficiency shortcut)\n",
    "    \n",
    "    if( gridGeom[nG].intersection(MAP).area > 0.0001) : #don't bother w grids off the map\n",
    "        for t in range(nTracts):\n",
    "            # if (t%3000 == 0) :\n",
    "            #    print (\"grid {0}, tract no {1}, ({2},{3})\".format(nG,t,tractGeom[t].centroid.x,tractGeom[t].centroid.y) )\n",
    "            intersxnArea = 0.\n",
    "            if tractGeom[t].geom_type == clipPoly.geom_type :  # tract is a simple polygon\n",
    "                intersxnArea = gridGeom[nG].intersection(tractGeom[t]).area  #replaced tractGeom w cleanedPoly\n",
    "            else : #tract is a multiPolygon, do the polygon intersections individually\n",
    "                #print(\"I think tract\",t,\"is a multiPolygon\")\n",
    "                for geom in tractGeom[t].geoms :\n",
    "                    intersxnArea += gridGeom[nG].intersection(geom).area\n",
    "            if (intersxnArea > 0 and tractPop[t] > minTractPop) : # this tract is at least partially in this grid and populated \n",
    "                if (tractArea[t] == 0):  #should not happen, but debugging\n",
    "                    print(t,tractGeom[t].centroid.x, tractGeom[t].centroid.y)  #debug print\n",
    "                gridPop[nG] += tractPop[t]*intersxnArea/tractArea[t]\n",
    "                if tractPop[t] > (1.0 * avgDistrictPop) :  #flag if we have a mega tract\n",
    "                    uhoh = input(\"Uh oh! We have a tract that's bigger than a district.  What now?\")\n",
    "                else :\n",
    "                    gridTractNo[nG][counter] = t  #add this tract to this grid's list, update the no of tracts in grid\n",
    "                    counter +=1            \n",
    "                    nGridTracts[nG] = counter\n",
    "        # OK, now, loop over PRECINCTS to develop each grid's list of precincts (prev loop was for tracts)\n",
    "        counter = 0\n",
    "        for p in range(nPrecincts):\n",
    "            intersxnArea = 0.\n",
    "            if vtdGeom[p].geom_type == clipPoly.geom_type :  # precinct is a simple polygon\n",
    "                intersxnArea = gridGeom[nG].intersection(vtdGeom[p]).area  #replaced tractGeom w cleanedPoly\n",
    "            else : #precinct is a multiPolygon, do the polygon intersections individually\n",
    "                for geom in vtdGeom[p].geoms :\n",
    "                    intersxnArea += gridGeom[nG].intersection(geom).area\n",
    "            intersxnArea = gridGeom[nG].intersection(vtdGeom[p]).area\n",
    "            if (intersxnArea > 0 and vtdPop[p] >0) : # this precinct is at least partially in this grid and recorded votes                 \n",
    "                gridPrecinctNo[nG][counter] = p  #add this precinct to this grid's list, update the no of tracts in grid\n",
    "                counter +=1            \n",
    "                nGridPrecincts[nG] = counter\n",
    "    gridDensity[nG] = gridPop[nG] / gridGeom[nG].area  #finished loop over tracts & vtd's.  Calceach grid's population density    \n",
    "\n",
    "minGridPop = np.min(gridPop)\n",
    "# avgGridPop = np.mean(gridPop)   #see below for explicit averaging, since there are so many empty grids\n",
    "maxGridPop = np.max(gridPop)\n",
    "nPopulatedGrids = 0.\n",
    "totPopulatedGridArea = 0.\n",
    "for nG in range(nGrids) :\n",
    "    if gridPop[nG] > 0. :\n",
    "        nPopulatedGrids +=1\n",
    "        totPopulatedGridArea += gridGeom[nG].area\n",
    "avgGridPop = np.sum(tractPop) / nPopulatedGrids\n",
    "avgGridDensity = np.sum(tractPop) / totPopulatedGridArea\n",
    "#avgGridDensity = np.average(gridDensity) #avgGridPop / (gridPL * gridPL) #these densities help home district algorithm\n",
    "maxGridDensity = np.max(gridDensity)\n",
    "print(\"done building grids. avgGridDensity, maxGridDensity,nPopulatedGrids =\",avgGridDensity,maxGridDensity,nPopulatedGrids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "808f513f-21af-4b03-8061-fdeeed33dafd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a heat map of grid density \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here is a heat map of grid density \")\n",
    "xyGridDensity = [[0.]*nGridsX for x in range (nGridsY) ]   #flipping x and y to get right orientation in pixel grid\n",
    "for nG in range (nGrids) : #  create polygon shape for each grid square, compute grid-square population density\n",
    "    x = int(nG % nGridsY)\n",
    "    y = int(nG / nGridsY)\n",
    "    if gridDensity[nG] > 0 :  #avoid log zero\n",
    "        xyGridDensity[x][y]=np.log(gridDensity[nG])\n",
    "c=plt.pcolormesh(xyGridDensity)\n",
    "plt.colorbar(c)\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "4013f80b-4fc8-40a1-b708-ee29c29b3ffe",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.123874999986419e-07 8.071199499999216e-06\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(np.min(vtdArea), np.min(tractArea))\n",
    "minTractPop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ab450500-f1a4-4292-a2fe-71eb2217121d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am working on tract number 0 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 4\n",
      "we have 2 non-opposing shorted wedges for tract no 5\n",
      "I am working on tract number 20 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 21\n",
      "I am working on tract number 40 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 41 6.0 1 14.3 1.8081 306211.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 49 2.0 0 90.0 0.2738 69137.6\n",
      "we have 2 non-opposing shorted wedges for tract no 49\n",
      "we have 2 non-opposing shorted wedges for tract no 51\n",
      "I am working on tract number 60 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 64 3.0 3 90.0 0.3224 85073.9\n",
      "we have 2 non-opposing shorted wedges for tract no 64\n",
      "we have 2 non-opposing shorted wedges for tract no 68\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 75 2.0 1 90.0 0.2508 71889.3\n",
      "we have 2 non-opposing shorted wedges for tract no 77\n",
      "we have 2 non-opposing shorted wedges for tract no 78\n",
      "I am working on tract number 80 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 81 9.0 1 -272.4 0.2949 184946.2\n",
      "I am working on tract number 100 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 100\n",
      "I am working on tract number 120 of 2198 tracts\n",
      "I am working on tract number 140 of 2198 tracts\n",
      "I am working on tract number 160 of 2198 tracts\n",
      "I am working on tract number 180 of 2198 tracts\n",
      "I am working on tract number 200 of 2198 tracts\n",
      "I am working on tract number 220 of 2198 tracts\n",
      "I am working on tract number 240 of 2198 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 249 0 237847.77438698025 1.7343\n",
      "8 yoyos for tract,wedge,wedgePop,r= 249 0 85183.4896076654 0.8671\n",
      "9 yoyos for tract,wedge,wedgePop,r= 249 0 238391.56481994494 1.7402\n",
      "10 yoyos for tract,wedge,wedgePop,r= 249 0 130235.1483147699 1.3037\n",
      "10 yoyos for tract,wedge,wedgePop,r= 249 0 150497.63738388082 1.5219\n",
      "11 yoyos for tract,wedge,wedgePop,r= 249 0 210730.337002859 1.6311\n",
      "12 yoyos for tract,wedge,wedgePop,r= 249 0 169865.4079178946 1.5765\n",
      "12 yoyos for tract,wedge,wedgePop,r= 249 0 187258.0732587208 1.6038\n",
      "13 yoyos for tract,wedge,wedgePop,r= 249 0 200577.19609393776 1.6174\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_3942/3637993524.py:68: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  minR = (avgDistrictPop / maxStartDensity / pi)**0.5   # conservative estimated radius of this tract's district\n",
      "/tmp/ipykernel_3942/3637993524.py:101: RuntimeWarning: invalid value encountered in multiply\n",
      "  wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)  #max prevents rare div-by-zero\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am working on tract number 260 of 2198 tracts\n",
      "I am working on tract number 280 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 281 7.0 0 88.6 1.2112 201839.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 281 8.0 0 88.6 1.1855 201839.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 281 9.0 0 88.6 1.1604 201839.8\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 281 10.0 0 88.6 1.1357 201839.8\n",
      "I am working on tract number 300 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 316 3.0 3 90.0 1.5799 319435.7\n",
      "I am working on tract number 320 of 2198 tracts\n",
      "I am working on tract number 340 of 2198 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 350 1 277562.3893549638 2.1421\n",
      "8 yoyos for tract,wedge,wedgePop,r= 350 1 43725.59765935122 1.0711\n",
      "9 yoyos for tract,wedge,wedgePop,r= 350 1 372814.7885763054 2.4595\n",
      "10 yoyos for tract,wedge,wedgePop,r= 350 1 96447.67941335007 1.7653\n",
      "11 yoyos for tract,wedge,wedgePop,r= 350 1 257644.73087025507 2.1124\n",
      "12 yoyos for tract,wedge,wedgePop,r= 350 1 121319.5787775777 1.9388\n",
      "12 yoyos for tract,wedge,wedgePop,r= 350 1 158113.5663780659 2.0256\n",
      "12 yoyos for tract,wedge,wedgePop,r= 350 1 205435.64395993078 2.069\n",
      "12 yoyos for tract,wedge,wedgePop,r= 350 1 238435.36059102183 2.0907\n",
      "I am working on tract number 360 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 363 9.0 0 87.6 1.3085 207523.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 363 10.0 0 87.6 1.2541 207523.0\n",
      "I am working on tract number 380 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 389 5.0 0 90.0 0.7082 199390.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 389 6.0 0 90.0 0.6996 199390.9\n",
      "I am working on tract number 400 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 407\n",
      "I am working on tract number 420 of 2198 tracts\n",
      "I am working on tract number 440 of 2198 tracts\n",
      "I am working on tract number 460 of 2198 tracts\n",
      "I am working on tract number 480 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 490 9.0 0 89.5 1.2047 197661.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 490 10.0 0 89.5 1.1979 197661.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 490 11.0 0 89.5 1.1911 197661.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 490 12.0 0 89.5 1.1843 197661.6\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 490 13.0 0 89.5 1.1776 197661.6\n",
      "we have 2 non-opposing shorted wedges for tract no 493\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 495 4.0 0 121.0 0.338 93131.8\n",
      "I am working on tract number 500 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 519\n",
      "I am working on tract number 520 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 520\n",
      "we have 2 non-opposing shorted wedges for tract no 538\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 539 4.0 1 90.0 0.2943 130441.0\n",
      "we have 2 non-opposing shorted wedges for tract no 539\n",
      "I am working on tract number 540 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 551\n",
      "we have 2 non-opposing shorted wedges for tract no 552\n",
      "I am working on tract number 560 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 563\n",
      "I am working on tract number 580 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 581 12.0 0 143.3 1.5598 819060.2\n",
      "I am working on tract number 600 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 612 5.0 3 90.0 2.5591 215279.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 612 6.0 3 90.0 2.3847 215279.7\n",
      "I am working on tract number 620 of 2198 tracts\n",
      "I am working on tract number 640 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 653\n",
      "I am working on tract number 660 of 2198 tracts\n",
      "I am working on tract number 680 of 2198 tracts\n",
      "I am working on tract number 700 of 2198 tracts\n",
      "I am working on tract number 720 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 723\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 724 7.0 1 -272.4 0.3019 139458.5\n",
      "I am working on tract number 740 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 749 6.0 2 90.0 0.3856 174995.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 752 5.0 3 90.0 0.2782 177370.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 752 6.0 3 90.0 0.2998 177370.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 752 7.0 3 90.0 0.323 177370.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 752 8.0 3 90.0 0.348 177370.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 752 9.0 3 90.0 0.375 177370.9\n",
      "we have 2 non-opposing shorted wedges for tract no 753\n",
      "we have 2 non-opposing shorted wedges for tract no 757\n",
      "we have 2 non-opposing shorted wedges for tract no 758\n",
      "I am working on tract number 760 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 774\n",
      "we have 2 non-opposing shorted wedges for tract no 779\n",
      "I am working on tract number 780 of 2198 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 791 0 251234.74532838375 1.0115\n",
      "8 yoyos for tract,wedge,wedgePop,r= 791 0 116543.65892712696 0.5057\n",
      "9 yoyos for tract,wedge,wedgePop,r= 791 0 251235.8737018137 1.0115\n",
      "10 yoyos for tract,wedge,wedgePop,r= 791 0 156212.64859448766 0.7586\n",
      "11 yoyos for tract,wedge,wedgePop,r= 791 0 236863.6375484853 0.8851\n",
      "11 yoyos for tract,wedge,wedgePop,r= 791 0 203424.94030619005 0.8218\n",
      "12 yoyos for tract,wedge,wedgePop,r= 791 0 178864.18757429512 0.7902\n",
      "12 yoyos for tract,wedge,wedgePop,r= 791 0 188904.28919865738 0.806\n",
      "I am working on tract number 800 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 803 2.0 3 90.0 0.876 179075.4\n",
      "we have 2 non-opposing shorted wedges for tract no 816\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 818 3.0 3 52.1 0.8502 247869.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 818 4.0 3 52.1 0.7094 247869.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 818 5.0 3 52.1 0.6384 247869.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 818 6.0 3 52.1 0.5745 247869.5\n",
      "I am working on tract number 820 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 825\n",
      "I am working on tract number 840 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 855\n",
      "I am working on tract number 860 of 2198 tracts\n",
      "I am working on tract number 880 of 2198 tracts\n",
      "I am working on tract number 900 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 914 6.0 2 90.0 0.4175 182675.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 914 7.0 2 90.0 0.4403 182675.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 914 8.0 2 90.0 0.4642 182675.7\n",
      "we have 2 non-opposing shorted wedges for tract no 919\n",
      "I am working on tract number 920 of 2198 tracts\n",
      "I am working on tract number 940 of 2198 tracts\n",
      "I am working on tract number 960 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 964\n",
      "I am working on tract number 980 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 984\n",
      "I am working on tract number 1000 of 2198 tracts\n",
      "I am working on tract number 1020 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1026 9.0 0 93.5 0.5271 197146.6\n",
      "we have 2 non-opposing shorted wedges for tract no 1029\n",
      "I am working on tract number 1040 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1052\n",
      "we have 2 non-opposing shorted wedges for tract no 1053\n",
      "we have 2 non-opposing shorted wedges for tract no 1054\n",
      "I am working on tract number 1060 of 2198 tracts\n",
      "I am working on tract number 1080 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1085\n",
      "we have 2 non-opposing shorted wedges for tract no 1087\n",
      "we have 2 non-opposing shorted wedges for tract no 1088\n",
      "we have 2 non-opposing shorted wedges for tract no 1092\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1095 4.0 1 90.0 0.631 166050.5\n",
      "I am working on tract number 1100 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1103 2.0 1 90.0 0.7258 376541.4\n",
      "we have 2 non-opposing shorted wedges for tract no 1106\n",
      "I am working on tract number 1120 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1129 11.0 0 83.4 0.6393 194209.6\n",
      "I am working on tract number 1140 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1147 5.0 1 38.8 0.7735 627281.5\n",
      "we have 2 non-opposing shorted wedges for tract no 1150\n",
      "I am working on tract number 1160 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1179\n",
      "I am working on tract number 1180 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1184 4.0 0 143.5 1.8167 282592.6\n",
      "we have 2 non-opposing shorted wedges for tract no 1197\n",
      "I am working on tract number 1200 of 2198 tracts\n",
      "I am working on tract number 1220 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1224 3.0 2 90.0 0.4666 421928.7\n",
      "I am working on tract number 1240 of 2198 tracts\n",
      "I am working on tract number 1260 of 2198 tracts\n",
      "I am working on tract number 1280 of 2198 tracts\n",
      "I am working on tract number 1300 of 2198 tracts\n",
      "I am working on tract number 1320 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1326 11.0 1 61.8 1.1599 232390.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1326 12.0 1 61.8 1.0186 232390.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1326 13.0 1 61.8 0.8945 232390.3\n",
      "I am working on tract number 1340 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1351 7.0 0 83.3 0.726 213210.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1351 8.0 0 83.3 0.6816 213210.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 9.0 0 89.1 1.105 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 10.0 0 89.1 1.0836 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 11.0 0 89.1 1.0625 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 12.0 0 89.1 1.0419 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 13.0 0 89.1 1.0216 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1353 14.0 0 89.1 1.0018 201349.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1355 5.0 0 110.6 0.6517 237177.2\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1356 2 214553.69955414883 2.4269\n",
      "loop31.0, tr1356,wedgePops783545.18, 152789.7, 210323.2, 210175.3, 210256.9, Overedge?1, 0, 0, 0, ,Satisfied?0010,yoyo?0200 \n",
      "   targetWP, latest drx4 are tWP,dr, 210625.7,0.2964, 210625.7,0.0025, 210625.7,0.0013, 210625.7,0.0147\n",
      "I am working on tract number 1360 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 3.0 0 83.3 0.8809 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 4.0 0 83.3 0.7948 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 5.0 0 83.3 0.7171 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 6.0 0 83.3 0.6469 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 7.0 0 83.3 0.5837 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 8.0 0 83.3 0.5266 224480.0\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1370 9.0 0 83.3 0.4751 224480.0\n",
      "I am working on tract number 1380 of 2198 tracts\n",
      "I am working on tract number 1400 of 2198 tracts\n",
      "I am working on tract number 1420 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1422 3.0 3 37.1 0.2797 358063.6\n",
      "I am working on tract number 1440 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1456 4.0 3 37.1 1.7604 302352.9\n",
      "I am working on tract number 1460 of 2198 tracts\n",
      "I am working on tract number 1480 of 2198 tracts\n",
      "I am working on tract number 1500 of 2198 tracts\n",
      "I am working on tract number 1520 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1520 13.0 3 36.0 2.3994 357392.1\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1526 4.0 3 86.8 0.7785 309195.5\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1526 5.0 3 86.8 0.5409 309195.5\n",
      "I am working on tract number 1540 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1541\n",
      "I am working on tract number 1560 of 2198 tracts\n",
      "I am working on tract number 1580 of 2198 tracts\n",
      "I am working on tract number 1600 of 2198 tracts\n",
      "I am working on tract number 1620 of 2198 tracts\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1628 3 441033.3293936313 2.3065\n",
      "8 yoyos for tract,wedge,wedgePop,r= 1628 3 87903.9126040428 1.1533\n",
      "9 yoyos for tract,wedge,wedgePop,r= 1628 3 441085.61390056415 2.3223\n",
      "10 yoyos for tract,wedge,wedgePop,r= 1628 3 166824.4368521638 1.7378\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1628 3 413789.81543586694 2.03\n",
      "11 yoyos for tract,wedge,wedgePop,r= 1628 3 262111.8085785741 1.8839\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1628 3 198340.99667959474 1.8108\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1628 3 227641.4063204063 1.8474\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1628 3 243644.94455970023 1.8656\n",
      "12 yoyos for tract,wedge,wedgePop,r= 1628 3 252530.77242757613 1.8748\n",
      "I am working on tract number 1640 of 2198 tracts\n",
      "I am working on tract number 1660 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1667\n",
      "I am working on tract number 1680 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1680\n",
      "we have 2 non-opposing shorted wedges for tract no 1685\n",
      "we have 2 non-opposing shorted wedges for tract no 1686\n",
      "we have 2 non-opposing shorted wedges for tract no 1687\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1688 2.0 3 90.0 0.3501 217425.9\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1688 3.0 3 90.0 0.3238 217425.9\n",
      "I am working on tract number 1700 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1703\n",
      "we have 2 non-opposing shorted wedges for tract no 1712\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1715 4.0 3 36.2 1.8069 284452.8\n",
      "I am working on tract number 1720 of 2198 tracts\n",
      "I am working on tract number 1740 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1741 6.0 2 90.0 2.3241 306387.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1741 10.0 2 90.0 2.3107 306387.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1741 14.0 2 90.0 3.6564 306387.4\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1741 15.0 2 90.0 2.5603 306387.4\n",
      "we have 2 non-opposing shorted wedges for tract no 1755\n",
      "I am working on tract number 1760 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1779\n",
      "I am working on tract number 1780 of 2198 tracts\n",
      "we have 2 OPPOSING shorted wedges for tract no 1780\n",
      "I am working on tract number 1800 of 2198 tracts\n",
      "I am working on tract number 1820 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1835 2.0 0 90.0 0.164 248646.2\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1836 2.0 2 90.0 0.1356 200921.2\n",
      "I am working on tract number 1840 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1844 4.0 0 93.5 1.4146 240198.7\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1844 5.0 0 93.5 1.2103 240198.7\n",
      "we have 2 non-opposing shorted wedges for tract no 1853\n",
      "I am working on tract number 1860 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1869\n",
      "we have 2 non-opposing shorted wedges for tract no 1873\n",
      "I am working on tract number 1880 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1887 4.0 0 90.0 0.3691 137656.6\n",
      "we have 2 non-opposing shorted wedges for tract no 1890\n",
      "I am working on tract number 1900 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1919\n",
      "I am working on tract number 1920 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1926 3.0 3 -272.4 0.4995 751192.1\n",
      "we have 2 non-opposing shorted wedges for tract no 1928\n",
      "we have 2 non-opposing shorted wedges for tract no 1930\n",
      "I am working on tract number 1940 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 1949\n",
      "we have 2 non-opposing shorted wedges for tract no 1950\n",
      "we have 2 non-opposing shorted wedges for tract no 1952\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 1955 16.0 1 46.3 4.4665 303794.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 1955 1 303794.6279759427 4.8201\n",
      "I am working on tract number 1960 of 2198 tracts\n",
      "I am working on tract number 1980 of 2198 tracts\n",
      "I am working on tract number 2000 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2007 2.0 1 90.0 0.8436 249758.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2007 3.0 1 90.0 0.6997 249758.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2007 4.0 1 90.0 0.5803 249758.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2007 5.0 1 90.0 0.4813 249758.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2007 6.0 1 90.0 0.3991 249758.3\n",
      "we have 2 non-opposing shorted wedges for tract no 2012\n",
      "I am working on tract number 2020 of 2198 tracts\n",
      "I am working on tract number 2040 of 2198 tracts\n",
      "we have 2 non-opposing shorted wedges for tract no 2040\n",
      "I am working on tract number 2060 of 2198 tracts\n",
      "I am working on tract number 2080 of 2198 tracts\n",
      "I am working on tract number 2100 of 2198 tracts\n",
      "I am working on tract number 2120 of 2198 tracts\n",
      "I am working on tract number 2140 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2143 4.0 1 90.0 1.2955 204980.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2143 5.0 1 90.0 1.2533 204980.3\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2143 6.0 1 90.0 1.2124 204980.3\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2143 1 204980.27903382375 1.1881\n",
      "I am working on tract number 2160 of 2198 tracts\n",
      "I am working on tract number 2180 of 2198 tracts\n",
      "we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop 2188 13.0 0 90.0 4.1237 313433.6\n",
      "7 yoyos for tract,wedge,wedgePop,r= 2188 0 313433.6267387041 4.7239\n",
      "Sum of weights over all precinct home districts should have been 1.000, but was  1.0001359450068785\n",
      "Average and max number of wedgePop loops per tract were:  7.329845313921747 31.0\n",
      "min,average,max of Home District areas were:  0.0 0.8945842365089723 3.2087067368435123\n",
      "All done.  We started, ended at 1691243650.8838768 with total elapsed hours of 0.665\n",
      "calculated statewide vote was 0.4491050636636472, should have been 0.4484531300060009\n",
      "calcd statewide Hispanic pop was 0.08714782629996094, should have been 0.09106954518080952\n",
      "calcd statewide Black pop was 0.17926088971677148, should have been 0.18412691729376815\n",
      "fraction of HDs that with altered wedge angles near boundaries =  0.5036396724294814\n"
     ]
    }
   ],
   "source": [
    "#3/13/22 - from HD2, but using coeff1, coeff2 (unrestricted opp wedge pop, wideAngle quadratic in ratio)\n",
    "#8/5/23 - rerun (now with 11 districts as intended for VA).  Only change is to add clock time\n",
    "# Bisect for yoyo > 3, precinct calcs after wedges finalized.  More aggressive Euler gain\n",
    "#minTractPop = 10  #this is set in a prior block\n",
    "startTime = time.time()\n",
    "pi=3.1415926536\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2*pi / nWedges\n",
    "wedgeTriAR = [math.sin(pi/nWedges)*math.cos(pi/nWedges)]*nWedges  #wedge triangle area ratio (= area / r*r)\n",
    "angle = [0.]*nWedges\n",
    "angle2 = [0.]*nWedges\n",
    "pt1 = [Point(0,0)]*nWedges  #these four define the polygon wedge for a growing home district\n",
    "pt2 = [Point(0,0)]*nWedges\n",
    "pt3 = [Point(0,0)]*nWedges\n",
    "pt4 = [Point(0,0)]*nWedges\n",
    "oldR = [0.]*nWedges  #wedge radius from previous loop\n",
    "# guessedR = [0.]*nWedges  #obsolete; was wedge radius if we extrapolate from population density of most recent wedge piece\n",
    "printPoly = [Polygon([(0,0),(0,1),(1,1)])]*nWedges #for debugging\n",
    "wedgePop = [0.]*nWedges\n",
    "tractLoopCounter = [0.]* nTracts  #this tracks how many loops per tract to get to target wedge Pop\n",
    "nearEdge = [0.]* nTracts   #not yet implemented; this will flag tracts near map edge for reprocessing\n",
    "tractUse = [0.] * nTracts  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "precinctUse = [0.] * nPrecincts   #same, but for each precinct / VTD\n",
    "loopTractUse = [0.] * nTracts  #same as above two, but only for the current loop / tract\n",
    "loopPrecinctUse = [0.] * nPrecincts\n",
    "HDvPop = [0.]*nTracts\n",
    "HDvGOP = [0.]*nTracts  #GOP lean of each tract's \"home district\"\n",
    "HDvBlack = [0.]*nTracts\n",
    "HDvHisp = [0.]*nTracts #pct Hispanic by home district\n",
    "HDweight = [0.]*nTracts  #relative weight of each district.  In absence of splits, will equal precinct pop\n",
    "HDarea = [0.]*nTracts  #geographical area of each home district\n",
    "HDradius = [[0.]*nWedges for t in range(nTracts)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nTracts)] #final included angle for each HD wedge\n",
    "angle0 = [-999.] * nTracts  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "toler = 0.005  #adjustable - fractional slop in district population.  normally 0.01, to be reduced to 0.005\n",
    "tolerPop = toler * avgDistrictPop  #absolute slop in district pop\n",
    "nLoopPrint = 30  #at this loop number, we alert user of problem\n",
    "nGiveUp = 40  #we punt after this many loops\n",
    "nLoopSuperPrint = nGiveUp - 2 # at this loop number, we output wedge growth visuals\n",
    "wrongPop = [0.]*nTracts\n",
    "normalGain = 0.8  #adjustable - a bit less than 1.0 for stability, how far we step relative to expected perfect guess\n",
    "EulerGain = 1.5 #if we hit empty land, gain more aggressively to get through it\n",
    "#yoyoFactor = 0.3 #rate of reduction in gain as solver continues to yoyo in solving a wedge  #not currently used ***\n",
    "globalMax_dr = (MAP.area/nDistricts) ** 0.5  #put a reasonable upper limit on wedge radial growth step size\n",
    "tractPrintInterval = 20  #for tracking progress\n",
    "minTractArea = 0.00001 * MAP.area / nTracts  #failsafe for later div-by-zero\n",
    "homePopDensity = avgGridDensity  #seed this\n",
    "didWeRestart = [0] * nTracts  #will flag if we adjusted wedge angles due to a single shorted wedge\n",
    "coeff1 = 0.3  #linear term. we will adjust this empirically to tighten tract weighting near boundaries\n",
    "coeff2 = 0.3  #quadratic term.  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "minWedgePop = [avgDistrictPop/nWedges] * nTracts  #wedge pop for wedge facing boundary (for tracts near boundaries)\n",
    "maxWideAngle = 0.8 * pi  #adjustable parameter.  (avoid wedges too close to half a pie\n",
    "\n",
    "for t in range(nTracts) :  #(nTracts):  #loop on each tract.  Start by resetting stats\n",
    "    gain = normalGain  #in case last precinct had convergence problems\n",
    "    if (t % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on tract number {0} of {1} tracts\".format(t,nTracts) )\n",
    "    tractLoopCounter[t] = 0.  #for stability stats, will track how many times we need to loop for each tract\n",
    "    # isActiveG = [0]*nGrids  #resets whether each grid is relevant to this tract (not used; see alt grid turn-on method)\n",
    "    if (tractArea[t] > minTractArea) :  #too lazy to indent everything.  We'll catch zero tractArea later\n",
    "        homePopDensity = tractPop[t]/tractArea[t]  #temporary - estimate the local density for initial step\n",
    "    tractCP = Point(tractGeom[t].centroid.x,tractGeom[t].centroid.y)  #shorthand for centroid of each tract\n",
    "    for nG in range(nGrids):\n",
    "        if gridGeom[nG].contains(tractCP) :  #which grid contains the centroid of this tract?  Turn it on!\n",
    "            # isActiveG[nG] = 1  #I don't think I use this\n",
    "            homeGridDensity = gridDensity[nG]\n",
    "    maxStartDensity = max(homePopDensity,homeGridDensity)\n",
    "    minR = (avgDistrictPop / maxStartDensity / pi)**0.5   # conservative estimated radius of this tract's district\n",
    "    tinyR = 0.01 * minR   #ensures we start with small, but not infinitesimal wedge populations\n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to our starting wedge\n",
    "    loopTractUse = [0.]*nTracts  #this and below help us reset tract n precinct use after a wedge reset\n",
    "    loopPrecinctUse = [0.]*nPrecincts\n",
    "    # ***GROW WEDGES SIMULTANEOUSLY via ARRAYS, SO WE CAN REACT ON FLY TO BOUNDARY STOPS\n",
    "    HDpop = 0.  #running total of this tract's \"home district\" population\n",
    "    nActiveWedges = nWedges #active wedges have not run over boudnary\n",
    "    targetWedgePop = [avgDistrictPop / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    #latestWedgeDensity = [0.]*nWedges  #stop using # pop'n density of the wedge piece we just added or subtracted\n",
    "    wedgePop = [0.]*nWedges\n",
    "    oldWedgePop = [0.]*nWedges  #wedge pop from previous round (needed for NR projection)\n",
    "    wedgePopGap = [0.]*nWedges\n",
    "    isOverEdge = [0] *nWedges #each wedge is still fully inside map boundary\n",
    "    isSatisfied = [0] * nWedges #wedges close enough to target are not improved upon\n",
    "    yoyoCount = [0] * nWedges #tracks how many times we've reversed this wedge's growth vs. shrink at current wPop target\n",
    "    wedgeMaxR = [0.] * nWedges #will track the largest radius this wedge has seen (to cap yoyo bisection step)\n",
    "    wedgeAngle = [avgWedgeAngle] * nWedges #reset to equi-angle when starting each tract    \n",
    "    currentR = [0.]*nWedges\n",
    "    old_dr = [0.]*nWedges\n",
    "    wedgeStop = 0  #obsolete? this will flag if we need to rejigger oldR when we stopped an over-boundary wedge\n",
    "    for nW in range(nWedges):\n",
    "        currentR[nW] = tinyR  #each wedge starts as a tiny triangle of this radius\n",
    "        old_dr[nW] = currentR[nW] #this will track the last radial step (to help convergence)\n",
    "    oldR = [0.]*nWedges   #for remembering last loop's wedge radius\n",
    "    max_dr = [globalMax_dr]*nWedges  #reset max possible positive radial step size\n",
    "    for nW in range(nWedges) :  #this loop: set up tiny wedges in each direction to seed each wedge loop\n",
    "        angle[nW] = (nW-0.5)*wedgeAngle[nW]+angle0[t]   #local variable for orientation of START of wedge\n",
    "        angle2[nW] = angle[nW]+wedgeAngle[nW]      #local angle for clockwise END of wedge\n",
    "        pt1[nW] = tractCP\n",
    "        pt2[nW] = Point(tractCP.x+currentR[nW]*math.cos(angle[nW]),  tractCP.y+currentR[nW]*math.sin(angle[nW]) )\n",
    "        pt3[nW] = Point(tractCP.x+currentR[nW]*math.cos(angle2[nW]), tractCP.y+currentR[nW]*math.sin(angle2[nW]) )\n",
    "        wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW] ]) #build a tiny starter wedge triangle\n",
    "        wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)  #max prevents rare div-by-zero\n",
    "    HDpop = np.sum(wedgePop)\n",
    "    if (tractPop[t] < minTractPop or tractArea[t] == 0 or isSkippedTract[t] == 1):\n",
    "        #go directly to jail, do not pass Go, this tract doesn't count\n",
    "        HDpop = avgDistrictPop  #white lie to kick us out of loop\n",
    "    while abs (HDpop - avgDistrictPop) > tolerPop :  #until we've grown the home district to the right size...\n",
    "        sumWedgePopGapChange = 0  #this will total wedge pops that fall short of expectations (when over boundary)\n",
    "        for nW in range(nWedges) :  #for each wedge, we'll build to gain pop or shrink to lose population ...\n",
    "            neededWedgePop = targetWedgePop[nW] - wedgePop[nW]\n",
    "            isSatisfied[nW] = 0  #default in case target changed last loop.  We'll check immediately below\n",
    "            if abs(neededWedgePop/targetWedgePop[nW]) < 0.5*toler :  #is this wedge close enough to stop iterating on it?\n",
    "                isSatisfied[nW] = 1\n",
    "            if isOverEdge[nW] == 0 and isSatisfied[nW] == 0:   #we skip over-boundary and near-perfect wedges\n",
    "                wedgePopDelta = wedgePop[nW] - oldWedgePop[nW]  #how much wedgePop gained in last loop\n",
    "                if (wedgePopDelta == 0): #our last wedge change was in an empty area (desert or off map)\n",
    "                    gainAdjust = EulerGain/gain  #Euler method often over-cautious at map edges or in sparse areas\n",
    "                    guessedRsquared = currentR[nW]*currentR[nW] * targetWedgePop[nW] / wedgePop[nW]  #Euler guess\n",
    "                    # can't use Newton-Raphson since last dy was zero, use Euler instead\n",
    "                    print(\"we hit a zero wedgePopDelta for tract, loop, wedge, wedgeAngle,r,pop\",t,tractLoopCounter[t],\n",
    "                          nW, round(180./pi*wedgeAngle[nW],1),round(currentR[nW],4),round(wedgePop[nW],1))\n",
    "                else: #use N-R estimation\n",
    "                    gainAdjust = 1.0\n",
    "                    R2delta = currentR[nW]*currentR[nW] - oldR[nW]*oldR[nW]  #this and below are run/rise of current slope\n",
    "                    guessedRsquared = currentR[nW]*currentR[nW] + R2delta / wedgePopDelta * neededWedgePop\n",
    "                    \n",
    "                guessedRsquared = max( guessedRsquared, 0. ) #minimum guardrail\n",
    "                guessed_dr = guessedRsquared ** 0.5 - currentR[nW]  #best guess for wedge radius change\n",
    "                #gain = max(0.3,normalGain ** (1. + yoyoFactor * yoyoCount[nW]))  #obsolete; using bisect\n",
    "                dr = gain * gainAdjust * guessed_dr   #gain typically ~0.8 for stability\n",
    "                dr = max( -0.5*currentR[nW],min(dr,max_dr[nW]) )  #apply min and max guardrails to wedge radius change\n",
    "                \n",
    "                if np.sign(dr) != np.sign(old_dr[nW]) :  #are we yoyoing? How many times?\n",
    "                    yoyoCount[nW] += 1\n",
    "                if yoyoCount[nW] > 3 and yoyoCount[nW] <= 6 :\n",
    "                    wedgeMaxR[nW] = max(wedgeMaxR[nW],currentR[nW]) #will track largest R in yoyo cycle\n",
    "                    max_dr[nW] = 2.*wedgeMaxR[nW]  #this will now store a reasonable max bisection step size\n",
    "                if yoyoCount[nW] > 6 :  #switch to bisection method; too many yo-yo's\n",
    "                    print(yoyoCount[nW],\"yoyos for tract,wedge,wedgePop,r=\",t,nW,wedgePop[nW],round(currentR[nW],4) )\n",
    "                    max_dr[nW] = 0.5 * max_dr[nW] #we are now bisecting ...\n",
    "                    if(neededWedgePop < 0):\n",
    "                        dr = max(-1.*max_dr[nW], -0.5*currentR[nW])  #reduce wedge size\n",
    "                    else:\n",
    "                        dr = max_dr[nW]  #increase wedge size\n",
    "                old_dr[nW] = dr  #these three lines -- save current as old values for next loop\n",
    "                oldR[nW] = currentR[nW]\n",
    "                oldWedgePop[nW] = wedgePop[nW]\n",
    "                if dr > 0. :  #we are growing a wedge trapezoid piece \n",
    "                    outerR = currentR[nW] + dr\n",
    "                    innerR = currentR[nW]\n",
    "                    currentR[nW] = outerR    #for next loop around\n",
    "                else:    #this wedge trapezoid piece will be SUBTRACTED from current wedge\n",
    "                    outerR = currentR[nW]\n",
    "                    innerR = currentR[nW] + dr  #remember, dr is negative here\n",
    "                    currentR[nW] = innerR             #for next loop around\n",
    "                #now, describe the new wedge to probe for precinct intersections ...\n",
    "                pt1[nW] = Point(tractCP.x+innerR*math.cos(angle[nW]), tractCP.y+innerR*math.sin(angle[nW]) )\n",
    "                pt2[nW] = Point(tractCP.x+outerR*math.cos(angle[nW]), tractCP.y+outerR*math.sin(angle[nW]) )\n",
    "                pt3[nW] = Point(tractCP.x+outerR*math.cos(angle2[nW]),tractCP.y+outerR*math.sin(angle2[nW]) )\n",
    "                pt4[nW] = Point(tractCP.x+innerR*math.cos(angle2[nW]),tractCP.y+innerR*math.sin(angle2[nW]) )\n",
    "                wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW],pt4[nW]])  #true for wedge add-on or to-be-trimmed\n",
    "                \n",
    "                printPoly[nW] = wedgePoly  #for debugging\n",
    "                latestWedgePop = 0.  #for the new piece, not the entire triangle\n",
    "                usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "                usedPrecinct = [0]*nPrecincts\n",
    "                for nG in range(nGrids) :  # loop over ACTIVE grids to look for intersecting tracts\n",
    "                    gridIntersxn = gridGeom[nG].intersection(wedgePoly)\n",
    "                    if (gridIntersxn.area > 0) :  #this grid is RELEVANT to this wedge\n",
    "                        for tt in range(nGridTracts[nG]) : #look for intersxns with all tracts in this grid\n",
    "                            nTT = gridTractNo[nG][tt] #shorthand for this tract's global tract no\n",
    "                            if(usedTract[nTT] == 0) :  #Did we not already look at this tract in another grid list?\n",
    "                                usedTract[nTT] = 1  #well, now we have!  Probe intersection with wedge\n",
    "                                overlap = tractGeom[nTT].intersection(wedgePoly).area\n",
    "                                if overlap > 0 :\n",
    "                                    fracArea = overlap/tractArea[nTT]\n",
    "                                    latestWedgePop  += fracArea*tractPop[nTT]  #always positive (used in density calc)\n",
    "                                    loopTractUse[nTT] += np.sign(dr)*overlap/tractArea[nTT] * tractPop[t]/avgDistrictPop\n",
    "                        # found all possible tract overlaps with this increment / decrement to this wedge.\n",
    "                        \n",
    "                wedgePop[nW] += np.sign(dr)*latestWedgePop  #for full triangle, based on this latest piece\n",
    "                # Now, flag if we're beyond boundary\n",
    "                if wedgePop[nW] < targetWedgePop[nW] : #if growing, confirm we're not beyond MAP boundary\n",
    "                    leadingEdge = LineString([pt2[nW],pt3[nW]])\n",
    "                    if leadingEdge.intersects(MAP) :  #still room to grow in part of edge, keep going\n",
    "                        gerrymandering = \"evil\"  #it had to be said\n",
    "                    else:  #this wedge is fully beyond the map. give up on more map intersection\n",
    "                        isOverEdge[nW] = 1\n",
    "                        shortedWedge = nW  #ID'ing highest numbered wedge that got shorted by the boundary in this loop\n",
    "                        oldWedgePopGap = wedgePopGap[nW]\n",
    "                        wedgePopGap[nW] = targetWedgePop[nW] - wedgePop[nW]  #how far this wedge's pop is below its target\n",
    "                        nActiveWedges -= 1  #a few lines below, we will adjust other wedge's targets\n",
    "                        sumWedgePopGapChange += wedgePopGap[nW] - oldWedgePopGap\n",
    "                        if (nActiveWedges == 0) : #we're doomed, somehow all wedges are short and off map\n",
    "                            print(\"PUNT! no more active wedges for tract, loop =\",t,tractLoopCounter[t] )\n",
    "                            tractLoopCounter[t] = nGiveUp + 1  #PUNT !!!\n",
    "                            \n",
    "                        max_dr = [globalMax_dr]*nWedges   #allow other wedges to take big steps again to catch up\n",
    "                        yoyoCount = [0] * nWedges  #go back to original gains on ALL active wedges\n",
    "                   \n",
    "        # end of nW loop to adjust all wedge populations by growing or trimming wedges, IDing over-edge wedges\n",
    "        tractLoopCounter[t] +=1   # still looping on home district Pop.\n",
    "        nReceivingWedges = nActiveWedges\n",
    "        oppFlag = 0\n",
    "        if 0 == 1: #always false; for HD2 we would have checked here for opp wedge restriction; ignore this block\n",
    "            # targetWedgePop[int(nWedges/2)] < 0.99 * avgDistrictPop/float(nWedges): #is opp wedge restricted?\n",
    "            oppFlag = 1\n",
    "            nReceivingWedges -= 1-isOverEdge[int(nWedges/2)]  #if yes, don't count opposite wedge as a receiver\n",
    "        if nReceivingWedges == 0: #rarely, the opposite wedge is the only active one\n",
    "            for nWW in range(nWedges): #in this case, we allow the opposite wedge to pick up the slack\n",
    "                targetWedgePop[nWW] += sumWedgePopGapChange/max(1.,float(nReceivingWedges) )\n",
    "        else: #if the opp wedge has a ceiling wedgePopTarget, distribute wedgePopGap to other active wedges\n",
    "            for nWW in range(nWedges):  #time to make adjustments in target wedge pops based on boundary fails\n",
    "                if nWW != int(nWedges/2) or oppFlag == 0 :  #excluding flagged opposite wedge as a receiver\n",
    "                    targetWedgePop[nWW] += sumWedgePopGapChange/float(nReceivingWedges)\n",
    "\n",
    "        # *** NEW 1/19/22 CODE TO ADJUST WEDGE ANGLES WHEN A BOUNDARY ENCOUNTERED\n",
    "        if (nActiveWedges == nWedges or nActiveWedges < nWedges - 2\n",
    "           or didWeRestart[t] == 1) :  #0 or 3+ over-boundary short wedges, or we've already adjusted wedge angles once\n",
    "            HDpop = np.sum(wedgePop) #Keep going with normal wedge growth and trim process\n",
    "        else :  # 1 OR 2 SHORTED WEDGES.  MAY WANT TO ALTER WEDGE ANGLES\n",
    "            didWeRestart[t] = 1  #to ensure we adjust wedge angles and target wedgePops at most once per tract\n",
    "            if (nActiveWedges == nWedges - 2) :  #exactly two wedges got shorted in this loop -- are they opposing?\n",
    "                oppW = int( (shortedWedge + nWedges/2) % nWedges)  #the index of wedge opposite the last shorted wedge\n",
    "                if (isOverEdge[oppW] == 0) :\n",
    "                    print(\"we have 2 non-opposing shorted wedges for tract no\",t)\n",
    "                    totalLiveAngle = 2.*pi - np.sum(isOverEdge)*avgWedgeAngle  #avail angle to divvy among live wedges  \n",
    "                    for nW in range (nWedges) : #Decrease wedge angles opposite shorted wedges via a complex weighting\n",
    "                        if isOverEdge[nW] == 0 :\n",
    "                            oppW = int( (nW + nWedges/2) % nWedges) \n",
    "                            angleWeight = (np.sum(wedgePopGap)-wedgePopGap[oppW])/np.sum(wedgePopGap)/(nActiveWedges-1)\n",
    "                            wedgeAngle[nW] = angleWeight * totalLiveAngle  \n",
    "                else : #shorted wedges ARE opposing\n",
    "                    print(\"we have 2 OPPOSING shorted wedges for tract no\",t) # no wedge-angle adjustment in this case\n",
    "                    #wedgeAngle=[avgWedgeAngle]*nWedges  #comment this out, no change\n",
    "            else: # a single shorted wedge (over boundary).  COMPLETELY RESTART wedge growth process\n",
    "                shortW = shortedWedge #Next dozen lines: convoluted code to find angle to closest boundary point\n",
    "                #print(\"1 wedge over map boundary for tract\",t,\"at loop, wedgePop\",tractLoopCounter[t],wedgePop[shortW] )\n",
    "                shortedPoly = Polygon([tractCP, pt2[shortW],pt3[shortW] ])\n",
    "                MAPedge = shortedPoly.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "                minDistance = max(tractCP.distance(MAPedge),tinyR)  #closest distance to edge where wedge hit the boundary\n",
    "                edgeCircle = tractCP.buffer(1.01*minDistance)  #build a circle a little bigger than this distance\n",
    "                #  1.001 is not big enough; will occasionally not intersect\n",
    "                closeArea = edgeCircle.intersection(MAPedge)\n",
    "                counter = 0.\n",
    "                maxCounter = 10. #give up after 10 tries\n",
    "                while closeArea.is_empty :  # protect against missing the map boundary somehow\n",
    "                    print(\"need to widen edge circle beyond\",minDistance, \"for tract (x,y)=(\",tractCP.x,tractCP.y)\n",
    "                    minDistance = minDistance * 1.1\n",
    "                    edgeCircle = tractCP.buffer(minDistance)  #widen the circle\n",
    "                    closeArea = edgeCircle.intersection(MAPedge)\n",
    "                    counter += 1\n",
    "                    if counter >= maxCounter: #not finding map edge intersection.  Try another way\n",
    "                        print(\"did not find boundary with circle approach.  Brute-force it.\")\n",
    "                        minDistance = tractCP.distance(MAP.exterior)\n",
    "                        edgeCircle = tractCP.buffer(1.01*minDistance)\n",
    "                        closeArea = edgeCircle.intersection(MAP.exterior)                        \n",
    "            \n",
    "                closePoint = closeArea.centroid  # this is a point very close to the closest beeline from tract to map edge\n",
    "                #print(closePoint,tractCP, \"are boundary point and tract center point\")\n",
    "                x1 = closePoint.x\n",
    "                x2 = tractCP.x  #debugging\n",
    "                dx = closePoint.x - tractCP.x\n",
    "                dy = closePoint.y - tractCP.y\n",
    "                exitAngle = pi/2. * np.sign(dy)  #default in case dx=0\n",
    "                if (dx != 0 ):\n",
    "                    exitAngle = math.atan(dy/dx)  #this is the angle from the x-axis to the exit beeline\n",
    "                    if dx < 0 :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                        exitAngle = pi + exitAngle\n",
    "                angle0[t] = exitAngle # this reorients 0th wedge to face boundary's closest point               \n",
    "                # New 1/23/22 - let's estimate wedgePopGap at ideal orientation, normal angle   # ****************\n",
    "                wedgeAngle1 = exitAngle - 0.5*avgWedgeAngle\n",
    "                wedgeAngle2 = exitAngle + 0.5*avgWedgeAngle\n",
    "                maxR = max(stateWidth,stateHeight) #ensuring we make a big enough wedge\n",
    "                wedgePt1 = tractCP\n",
    "                wedgePt2 = Point(tractCP.x+maxR*math.cos(wedgeAngle1),  tractCP.y+maxR*math.sin(wedgeAngle1) )\n",
    "                wedgePt3 = Point(tractCP.x+maxR*math.cos(wedgeAngle2), tractCP.y+maxR*math.sin(wedgeAngle2) )\n",
    "                wedgePoly = Polygon([ wedgePt1, wedgePt2, wedgePt3 ])\n",
    "                minWedgePop[t] = 0. #the wedgePop of the shorted wedge if we re-orient but don't adjust angles\n",
    "                usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "                for nG in range(nGrids) :  # loop over ACTIVE grids to look for intersecting tracts\n",
    "                    gridIntersxn = gridGeom[nG].intersection(wedgePoly)\n",
    "                    if (gridIntersxn.area > 0) :  #this grid is RELEVANT to this wedge\n",
    "                        for tt in range(nGridTracts[nG]) : #look for intersxns with all tracts in this grid\n",
    "                            nTT = gridTractNo[nG][tt] #shorthand for this tract's global tract no\n",
    "                            if(usedTract[nTT] == 0) :  #Did we not already look at this tract in another grid list?\n",
    "                                usedTract[nTT] = 1  #well, now we have!  Probe intersection with wedge\n",
    "                                overlap = tractGeom[nTT].intersection(wedgePoly).area\n",
    "                                if overlap > 0 :\n",
    "                                    fracArea = overlap/tractArea[nTT]\n",
    "                                    minWedgePop[t]  += fracArea*tractPop[nTT]  #always positive (used in density calc)\n",
    "                #print(\"the minimum shorted Wedge Pop for tract {0} is {1}\".format(t,minWedgePop[t]) )  #debug\n",
    "                #printAngle[t] = round(exitAngle*180./pi,4) #for debugging\n",
    "                printDist = round(minDistance,4)\n",
    "                #print(t,\"(\",tractCP.x,tractCP.y,\")\",printAngle,printDist,\"t,tract(x,y),exitAngle,dist\")\n",
    "                # ********************************************************************\n",
    "                # assign new wedge angles.  The two wide angles face toward and away from nearest boundary\n",
    "                #ratio = wedgePopGap[shortW]/ (avgDistrictPop/nWedges)  #0-1; this is degree of shortness\n",
    "                ratio = 1. - minWedgePop[t]/ (avgDistrictPop/nWedges)  # *** UPDATED\n",
    "                # printWedgePopGap[t] = wedgePopGap[shortW]\n",
    "                wideAngle = (1. + coeff1 * ratio + coeff2 * ratio*ratio)*avgWedgeAngle #HERE, WE ADJUST ANGLES\n",
    "                wideAngle = min(wideAngle, maxWideAngle*pi) #set an upper limit\n",
    "                thinAngle = (2.*pi - 2.*wideAngle)/(nWedges - 2.)  #other wedges equally angle-compressed\n",
    "                #if (t % 9 == 0):  #occasional print\n",
    "                    #print(\"tract,wide, thin angles are \",t,round(180/pi*wideAngle,4),round(180/pi*thinAngle,4) )\n",
    "                for nW in range(nWedges) :\n",
    "                    if (nW == 0 or nW == int(nWedges/2) ) : #assign these two as shorted wedge and its opposite\n",
    "                        wedgeAngle[nW] = wideAngle\n",
    "                    else :\n",
    "                        wedgeAngle[nW] = thinAngle\n",
    "                #** COMPLETELY RESTART WEDGE GROWTH PROCESS FROM INITIAL PIZZA SLICES, NOW RE-ORIENTED\n",
    "                loopTractUse = [0.] * nTracts  # reset as we are starting over\n",
    "                loopPrecinctUse = [0.]* nPrecincts\n",
    "                HDpop = 0.\n",
    "                nActiveWedges = nWedges\n",
    "                targetWedgePop = [avgDistrictPop/nWedges] * nWedges\n",
    "                oldR = [0.]*nWedges   #for remembering last loop's wedge radius  \n",
    "                currentR = [tinyR]*nWedges                \n",
    "                old_dr = [tinyR]*nWedges  #this will track the last radial step (to help convergence)\n",
    "                max_dr = [globalMax_dr]*nWedges  #reset max step size\n",
    "                wedgePop = [0.]*nWedges\n",
    "                oldWedgePop = [0.]*nWedges #wedge pop from previous round\n",
    "                wedgePopGap = [0.]*nWedges\n",
    "                isOverEdge = [0] *nWedges\n",
    "                isSatisfied = [0] *nWedges\n",
    "                yoyoCount = [0] *nWedges #just in case we missed this earlier\n",
    "                wedgeMaxR = [0.] * nWedges #resetting\n",
    "                angle[0] = angle0[t] - 0.5*wideAngle  #the 0th wedge always faces the boundary\n",
    "                angle2[0] = angle[0] + wedgeAngle[0]\n",
    "                for nW in range(nWedges) :\n",
    "                    if (nW == 0):\n",
    "                        angle[nW] = angle0[t] - 0.5*wideAngle  #we have to start somewhere :-)\n",
    "                    else :\n",
    "                        angle[nW] = angle2[nW-1]\n",
    "                    angle2[nW] = angle[nW]+wedgeAngle[nW]      \n",
    "                    pt1[nW] = tractCP\n",
    "                    pt2[nW] = Point(tractCP.x+tinyR*math.cos(angle[nW]),  tractCP.y+tinyR*math.sin(angle[nW]) )\n",
    "                    pt3[nW] = Point(tractCP.x+tinyR*math.cos(angle2[nW]), tractCP.y+tinyR*math.sin(angle2[nW]) )\n",
    "                    wedgePoly = Polygon([pt1[nW], pt2[nW], pt3[nW] ])\n",
    "                    wedgePop[nW] = tractPop[t]* wedgePoly.area/max(tractArea[t],minTractArea)\n",
    "                HDpop = np.sum(wedgePop)   #** END OF RESTART BLOCK.  RE-ENTER MAIN LOOP FOR THIS TRACT\n",
    "                      \n",
    "        # **** BELOW IS TO CORRECT FOR NONCONVERGENCE *****\n",
    "        if (tractLoopCounter[t] > nLoopPrint):  #may be becoming unstable. Alert user,    #and (don't) reduce gain\n",
    "            strPop = str(round(HDpop,2))\n",
    "            strWdg = \"Overedge?\"\n",
    "            strSat = \"Satisfied?\"\n",
    "            strYoyo = \"yoyo?\"                \n",
    "            strTWP_dr = \"tWP,dr\"\n",
    "            for nWW in range(nWedges) :\n",
    "                strPop = strPop + \", \"+str(round(wedgePop[nWW],1) )\n",
    "                strWdg = strWdg +str(isOverEdge[nWW])+\", \"\n",
    "                strSat = strSat +str(isSatisfied[nWW])\n",
    "                strYoyo = strYoyo + str(yoyoCount[nWW])\n",
    "                strTWP_dr = strTWP_dr + \", \"+str(round(targetWedgePop[nWW],1) )+\",\"+str(round(old_dr[nWW],4) )\n",
    "            print(\"loop{0}, tr{1},wedgePops{2}, {3},{4},{5} \".format(tractLoopCounter[t],t,strPop,strWdg,strSat,strYoyo) )\n",
    "            print(\"   targetWP, latest drx4 are\",strTWP_dr)\n",
    "\n",
    "        if (tractLoopCounter[t] > nLoopSuperPrint) :\n",
    "            for nWW in range(nWedges):                \n",
    "                print(\"wedge no, currentR,oldWedgePop, wedgePop, overEdge?\",nWW,str(round(currentR[nWW],5)), \n",
    "                      str(round(oldWedgePop[nWW],4)), str(round(wedgePop[nWW],4)),isOverEdge[nWW])   #debug\n",
    "                x, y = printPoly[nWW].exterior.xy     #wedge debugging .....\n",
    "                plt.plot(x, y, c=(0.1, 0.2, 0.02+float(nWW)/nWedges) )\n",
    "            plt.show()\n",
    "        if(tractLoopCounter[t] >= nGiveUp):\n",
    "            print(\"I looped {0} times on tract {1}, giving up w pop {2}\".format(nGiveUp,t,HDpop) )\n",
    "            wrongPop[t] = HDpop  #this will flag this HD as triaged\n",
    "            HDpop = avgDistrictPop  #white lie to kick out of loop\n",
    "        # *** END OF TRIAGE FOR NONCONVERGENCE\n",
    "        \n",
    "    # END OF WHILE LOOP --> we are within tolerance of avgDistrictPop. Finalize this tract's Home District stats\n",
    "    for nTT in range (nTracts) :\n",
    "        tractUse[nTT] += loopTractUse[nTT]\n",
    "    totGOP = 0.\n",
    "    totVote = 0.\n",
    "    totVAP = 0.\n",
    "    totHisp = 0.\n",
    "    totBlack = 0.  #zero these out prior to summing over final wedges\n",
    "    usedTract = [0]*nTracts  #rezero lists of tracts and precincts that could straddle multiple grids\n",
    "    usedPrecinct = [0]*nPrecincts\n",
    "\n",
    "    if (tractPop[t] < minTractPop or tractArea[t] == 0 or isSkippedTract[t] == 1): \n",
    "        #we bypassed the big loop; this tract is inconsequential\n",
    "        HDvPop[t] = HDpop  #a white lie\n",
    "        HDweight[t] = 0.000001  #to suppress this in total stats\n",
    "    else :\n",
    "        HDvPop[t] = np.sum(wedgePop)\n",
    "        # HDvHisp[t] = np.sum(wedgeHisp)/np.sum(wedgePop)  #3/2/22 - move to final wedge calcs\n",
    "        # HDvBlack[t] = np.sum(wedgeBlack)/np.sum(wedgePop)  #3/2/22 - move to final wedge calcs\n",
    "        HDweight[t] = tractPop[t]/np.sum(tractPop)\n",
    "        nearEdge[t] = nWedges - nActiveWedges  #flagging the number of wedges that were not completely pop-filled\n",
    "        centerPt = tractCP\n",
    "        outerPt2 = Point(tractCP.x+currentR[0]*math.cos(angle[0]), tractCP.y+currentR[0]*math.sin(angle[0]) )\n",
    "        outerPt3 = Point(tractCP.x+currentR[0]*math.cos(angle2[0]),tractCP.y+currentR[0]*math.sin(angle2[0]) )\n",
    "        HDpolly = Polygon([centerPt,outerPt2,outerPt3])   #initiate a polygon that will be the home district\n",
    "        for nW in range(nWedges):\n",
    "            HDradius[t][nW] = currentR[nW]\n",
    "            HDangle[t][nW] = angle[nW]\n",
    "            \n",
    "        for nW in range(1,nWedges):  #save final geometry, compute minority and partisan stats\n",
    "            cR = currentR[nW] #shorthand\n",
    "            outerPt2 = Point(tractCP.x+cR*math.cos(angle[nW]), tractCP.y+cR*math.sin(angle[nW]) )\n",
    "            outerPt3 = Point(tractCP.x+cR*math.cos(angle2[nW]),tractCP.y+cR*math.sin(angle2[nW]) )\n",
    "            HDpolly =  HDpolly.union( Polygon([centerPt,outerPt2,outerPt3]) )  #add this wedge to HD district polygon\n",
    "        HDpolly = HDpolly.intersection(MAP)  #exclude map's convex hull and buffer, just the original union of precincts\n",
    "        HDarea[t] = HDpolly.area  #for stats, final Home District area\n",
    "        for nG in range(nGrids) :  # ID the ACTIVE grids to look for intersecting precincts\n",
    "            gridIntersxn = gridGeom[nG].intersection(HDpolly)\n",
    "            if (gridIntersxn.area > 0) :  #this grid is RELEVANT to the final Home District\n",
    "                for tt in range(nGridTracts[nG]):\n",
    "                    nTT = gridTractNo[nG][tt]\n",
    "                    if usedTract[nTT] == 0: #only examine tracts that have not already been called for intersection\n",
    "                        usedTract[nTT] == 1  #this tract has now been called \n",
    "                        overlap = tractGeom[nTT].intersection(HDpolly).area\n",
    "                        if overlap > 0 :\n",
    "                            fracArea = overlap/tractArea[nTT]\n",
    "                            totVAP += fracArea*tractVAP[nTT]\n",
    "                            totHisp += fracArea*tractHisp[nTT]\n",
    "                            totBlack += fracArea*tractBlack[nTT]\n",
    "                        \n",
    "                for pp in range(nGridPrecincts[nG]): #scanning the list of precincts in this active grid\n",
    "                    nPP = gridPrecinctNo[nG][pp]\n",
    "                    if usedPrecinct[nPP] == 0  :\n",
    "                        usedPrecinct[nPP] = 1  #don't double up on precinct intersection\n",
    "                        overlap = vtdGeom[nPP].intersection(HDpolly).area\n",
    "                        if overlap > 0 :\n",
    "                            fracArea = overlap/vtdArea[nPP]\n",
    "                            totGOP += fracArea*vtdGOP[nPP]*vtdPop[nPP]\n",
    "                            totVote += fracArea*vtdPop[nPP]\n",
    "                            loopPrecinctUse[nPP] += overlap/vtdArea[nPP] *tractPop[t]/avgDistrictPop\n",
    "        HDvHisp[t] = totHisp/totVAP\n",
    "        HDvBlack[t] = totBlack/totVAP\n",
    "        HDvGOP[t] = totGOP / totVote\n",
    "        for nPP in range (nPrecincts) :\n",
    "            precinctUse[nPP] += loopPrecinctUse[nPP] #add to global use for this precinct\n",
    "            \n",
    "        \n",
    "\n",
    "    # end of loop on this tract\n",
    "for t in range(nTracts):\n",
    "    if(wrongPop[t] > 0):\n",
    "        HDvPop[t] = wrongPop[t]  #undo the lie that got us out of the loop early\n",
    "HDsumWeight = np.sum(HDweight)\n",
    "print(\"Sum of weights over all precinct home districts should have been 1.000, but was \",HDsumWeight)\n",
    "print(\"Average and max number of wedgePop loops per tract were: \",np.average(tractLoopCounter),np.max(tractLoopCounter) )\n",
    "print(\"min,average,max of Home District areas were: \",np.min(HDarea),np.average(HDarea),np.max(HDarea) )\n",
    "stateGOP2 = 0.\n",
    "stateHisp2 = 0.\n",
    "stateBlack2 = 0.\n",
    "for t in range(nTracts):\n",
    "    HDweight[t] = HDweight[t]/HDsumWeight   #renormalizing\n",
    "    stateGOP2 += HDweight[t]*HDvGOP[t]\n",
    "    stateBlack2 += HDweight[t]*HDvBlack[t]\n",
    "    stateHisp2 += HDweight[t]*HDvHisp[t]\n",
    "statePop = np.sum(tractPop)\n",
    "totalSeconds = time.time() - startTime\n",
    "print(\"All done.  We started, ended at\",startTime,\"with total elapsed hours of\",r3(totalSeconds/3600.) )\n",
    "print(\"calculated statewide vote was {0}, should have been {1}\".format(stateGOP2, stateGOP) )\n",
    "print(\"calcd statewide Hispanic pop was {0}, should have been {1}\".format(stateHisp2, np.sum(tractHisp)/stateVAP ) )\n",
    "print(\"calcd statewide Black pop was {0}, should have been {1}\".format(stateBlack2, np.sum(tractBlack)/stateVAP ) )\n",
    "print(\"fraction of HDs that with altered wedge angles near boundaries = \",np.sum(didWeRestart)/nTracts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "24a347a9-8220-4c1a-bcfc-14923f1f98f7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sum of weights over all precinct home districs should have been 1.000, but was  1.0001359450068785\n",
      "Average and max number of wedgePop loops per tract were:  7.329845313921747 31.0\n",
      "min,average,max of Home District areas were:  0.0 0.8945842365089723 3.2087067368435123 for  VA\n"
     ]
    }
   ],
   "source": [
    "print(\"Sum of weights over all precinct home districs should have been 1.000, but was \",HDsumWeight)\n",
    "print(\"Average and max number of wedgePop loops per tract were: \",np.average(tractLoopCounter),np.max(tractLoopCounter) )\n",
    "print(\"min,average,max of Home District areas were: \",np.min(HDarea),np.average(HDarea),np.max(HDarea),\"for \",STATE )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "72247942-899a-4ab2-9796-239aa1e524fb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VA 05Aug\n"
     ]
    }
   ],
   "source": [
    "date = \"05Aug\"  #19Mar\n",
    "print(STATE, date)  #check that I will not overwrite existing file :-)\n",
    "tractCPx = [0.]*nTracts\n",
    "tractCPy = [0.]*nTracts\n",
    "tractNo = [0.]*nTracts\n",
    "for t in range(nTracts):\n",
    "    tractCPx[t]=tractGeom[t].centroid.x\n",
    "    tractCPy[t]=tractGeom[t].centroid.y\n",
    "    tractNo[t]=t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "c55ac5fd-7402-47b9-9093-10b9fe0912b6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#LET'S WRITE AN OUTPUT FILE BEFORE WE FORGET :-)\n",
    "#convert HD wedge geometries to 1D arrays.  BELOW IS FOR 4-WEDGE.  CAN AUGMENT FOR 6-WEDGE\n",
    "HDangle0 = [0.]*nTracts\n",
    "HDradius0 = [0.]*nTracts\n",
    "HDangle1 = [0.]*nTracts\n",
    "HDradius1 = [0.]*nTracts\n",
    "HDangle2 = [0.]*nTracts\n",
    "HDradius2 = [0.]*nTracts\n",
    "HDangle3 = [0.]*nTracts\n",
    "HDradius3 = [0.]*nTracts\n",
    "for t in range(nTracts):\n",
    "    HDangle0[t] = HDangle[t][0]\n",
    "    HDradius0[t] = HDradius[t][0]\n",
    "    HDangle1[t] = HDangle[t][1]\n",
    "    HDradius1[t] = HDradius[t][1]\n",
    "    HDangle2[t] = HDangle[t][2]\n",
    "    HDradius2[t] = HDradius[t][2]\n",
    "    HDangle3[t] = HDangle[t][3]\n",
    "    HDradius3[t] = HDradius[t][3]\n",
    "# now convert output to pandas dataframe and export\n",
    "\n",
    "paramList = [\"STATE\",\"stateGOP\",\"nDistricts\",\"nTracts\",\"nPrecincts\",\"nWedges\",\"popn-toler\",\n",
    "             \"gain\",\"coeff1\",\"coeff2\"]\n",
    "paramValues = [STATE,stateGOP, nDistricts, nTracts,nPrecincts,nWedges, toler, gain, coeff1,coeff2]\n",
    "for i in range(nTracts-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "df = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"HD-pop\":HDvPop,\"HDvGOP\":HDvGOP,\"HDvHisp\":HDvHisp,\n",
    "                    \"HDvBlack\":HDvBlack,\"HDwt\":HDweight,\"HDarea\":HDarea, \"HDangle0\":HDangle0, \"HDangle1\":HDangle1,\n",
    "                    \"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\n",
    "                    \"HDradius2\":HDradius2,\"HDradius3\":HDradius3,\"startAngle\":angle0,\"tractNo\":tractNo,\n",
    "                    \"Loops\":tractLoopCounter,\"tractPop\":tractPop,\"tractHisp\":tractHisp,\"tractBlack\":tractBlack,\n",
    "                    \"centroid x\":tractCPx,\"centroid y\":tractCPy, \"tractUse\":tractUse,\"nearEdge\":nearEdge,\n",
    "                    \"wrongPop\":wrongPop,\"Restart?\":didWeRestart} ) \n",
    "\n",
    "outname = STATE+str(nDistricts)+\"HD1tol\"+str(toler)+\"nW\"+str(nWedges)+date+\".csv\"\n",
    "outpath = \"../state_HD_output/\"+outname   # may not need the \"../\"\n",
    "df.to_csv(outpath)\n",
    "precinctNo = [0.]*nPrecincts\n",
    "vtdX = [0.]*nPrecincts\n",
    "vtdY = [0.]*nPrecincts\n",
    "for p in range(nPrecincts):\n",
    "    precinctNo[p]=p\n",
    "    vtdX[p] = vtdGeom[p].centroid.x\n",
    "    vtdY[p] = vtdGeom[p].centroid.y\n",
    "df2 = pd.DataFrame( {\"precinctNo\":precinctNo,\"precinctPop\":vtdPop,\"precUse\":precinctUse, \"vtdX\":vtdX, \"vtdY\":vtdY} )\n",
    "outname2 = STATE+date+\"_VTD_tol\"+str(toler)+\"nW\"+str(nWedges)+\".csv\"\n",
    "outpath = \"../state_HD_output/\"+outname2  #\"state_HD_output/\"+outname2\n",
    "df2.to_csv(outpath)  #currently, I'm outputting the precinct use stats to a separate file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "c4449da0-47a9-40cc-a585-8288447290e6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will redo tract numbers  [0]\n"
     ]
    }
   ],
   "source": [
    "# Looking for nonconvergers ...  Run even if none observed, just to check  \n",
    "redo = [0]\n",
    "counter = 0.\n",
    "for t in range (nTracts) :\n",
    "    if wrongPop[t] > 0 :\n",
    "        ratio = round(wrongPop[t]/avgDistrictPop,2)\n",
    "        tractX = tractGeom[t].centroid.x\n",
    "        tractY = tractGeom[t].centroid.y        \n",
    "        print(t, ratio,\"(\",tractX,tractY,\")\",HDvGOP[t], \"t, pop/target,(x,y), pctR\")\n",
    "        if (ratio < 0.9 or ratio > 1.1) :  #these we will redo\n",
    "            plt.text(tractGeom[t].centroid.x, tractGeom[t].centroid.y,ratio, fontsize=14)\n",
    "            if counter == 0 :  #first redo\n",
    "                redo = [t]\n",
    "            else :\n",
    "                redo.append(t)\n",
    "            counter+= 1\n",
    "        else: #show these milder offenders on the map in a smaller font            \n",
    "            plt.text(tractGeom[t].centroid.x, tractGeom[t].centroid.y,ratio, fontsize=9)\n",
    "\n",
    "x,y = tractMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"purple\")\n",
    "plt.show()\n",
    "print(\"we will redo tract numbers \",redo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "be6e965b-4ca8-4af2-8031-63132fbb939d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "716 0.5506100750020834 394 pop,GOP 0.748730964467005\n",
      "717 0.4943021127212797 15929 pop,GOP 0.801996358842363\n",
      "718 0.44168088736099587 16094 pop,GOP 0.8025972412079035\n",
      "719 0.47468586645950767 15910 pop,GOP 0.8031426775612822\n",
      "721 0.4227034233763642 16048 pop,GOP 0.8027791625124626\n",
      "723 0.5677381753877088 268 pop,GOP 0.7052238805970149\n",
      "1811 0.5828250501276728 2773 pop,GOP 0.6141363144608727\n",
      "1812 0.5796295483167243 2738 pop,GOP 0.4579985390796202\n",
      "1853 0.584362403436536 2147 pop,GOP 0.6264555193292967\n",
      "1896 0.5978410636413196 1274 pop,GOP 0.6907378335949764\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting underused PRECINCTS\n",
    "for p in range (nPrecincts) :\n",
    "    if precinctUse[p] < 0.6 and isSkippedPrecinct[p] == 0 and vtdPop[p] > 0: #ignore suppressed precincts\n",
    "        print(p,precinctUse[p], vtdPop[p],\"pop,GOP\",vtdGOP[p])\n",
    "        pU = round(precinctUse[p],3)\n",
    "        tractX = vtdGeom[p].centroid.x\n",
    "        tractY = vtdGeom[p].centroid.y        \n",
    "        # print(t, ratio,\"(\",tractX,tractY,\")\",HDvGOP[t], \"t, pop/target,(x,y), pctR\")\n",
    "        plt.text(vtdGeom[p].centroid.x, vtdGeom[p].centroid.y,pU, fontsize=9)\n",
    "        plotPoly(vtdGeom[p])\n",
    "\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"purple\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "37f47a77-d58e-4b4c-be60-676819128e21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# (OPTIONAL) IF WE STOPPED AND RESTARTED, read the data back in:  #NEED TO UPDATE THIS W/ANGLES, RADII\n",
    "import pandas as pd\n",
    "infilename = \"FL_nD28tol0.01nW4.csv\"\n",
    "df2 = pd.read_csv(\"state_HD_output/\"+infilename)\n",
    "HDvPop = df2[\"HD-pop\"]\n",
    "HDvHisp = df2[\"HDvHisp\"]\n",
    "HDvGOP = df2['HDvGOP']\n",
    "HDweight = df2['HDwt']\n",
    "HDarea = df2['HDarea']\n",
    "tractLoopCounter = df2['Loops']\n",
    "tractPop = df2['tractPop']\n",
    "tractCPx = df2['centroid x']\n",
    "tractCPy = df2['centroid y']\n",
    "tractUse = df2['tractUse']\n",
    "# nearEdge = df2['nearEdge']   #add this back in, PLEASE\n",
    "df2.head()\n",
    "nTracts = len(tractPop)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "e9b2c0c0-fb53-44e5-9155-1963d4833ee8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "750596.7418101031 0.1131774380110593 0.0001361943772 0.0400616118781349 0.7450137754374908\n"
     ]
    }
   ],
   "source": [
    "#  HERE'S A BLOCK TO OVERWRITE THE REDONE DATA\n",
    "for r in range(nRedos):\n",
    "    t = redo[r]\n",
    "    HDvPop[t] = redoHDvPop[r]\n",
    "    HDvGOP[t] = redoHDvGOP[r]\n",
    "    tractArea[t] = redoHDarea[r]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "c80e0880-6811-4408-b847-6d70bd2546ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt   #SKIP THIS BLOCK IF STARTING FROM FIRST BLOCK\n",
    "from scipy.stats import norm\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "c8f73bb9-e36b-41c7-9220-1ec09169aa3e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# all done with redo's.  Let's look at some outputs.  First, red/blue by home district  SHOULD BE MIX OF RED AND BLUE\n",
    "nPlot = 5\n",
    "for t in range(nTracts):\n",
    "    if(t % nPlot == 0 and tractPop[t] > minTractPop):\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y,color='green')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "a5d3b510-6d1e-49ae-9a5d-03352e2b449e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "map of tracts that were used less than 0.7 of expectation in VA\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now, where are those UNDERPERFORMING tracts (<0.x usage)\n",
    "maxPlot = 0.70\n",
    "print(\"map of tracts that were used less than {0} of expectation in {1}\".format(maxPlot, STATE) )\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] < maxPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "\n",
    "x,y = wholeMAP.exterior.xy   #turn these on if I pull map back in\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "876011e8-d37e-44a6-8dd9-a1e4d2f51e58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a map of tracts that were used more than 1.2 of expectation\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... And where are the OVERUSED tracts?\n",
    "minPlot = 1.2\n",
    "print(\"here is a map of tracts that were used more than {0} of expectation\".format(minPlot) )\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] >minPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "19bfa7c8-0449-4182-8ed9-f5a1c1276f03",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is a map of 3 tracts that were used more than 1.6 of expectation\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... And where are the REALLY OVERUSED tracts?\n",
    "minPlot = 1.6\n",
    "counter = 0\n",
    "for t in range(nTracts):\n",
    "    if(tractUse[t] >minPlot and tractUse[t] > 0.05):  #ignore skipped tracts\n",
    "        redd = min(max( 0, ( HDvGOP[t] - 0.5) * 3.0 ),1)\n",
    "        bluu = min(max( 0, (0.5 - HDvGOP[t]) * 3.0 ),1)\n",
    "        plt.scatter(tractCPx[t],tractCPy[t],marker='.',color=(redd, 0,bluu ) )\n",
    "        counter +=1\n",
    "\n",
    "print(\"here is a map of {0} tracts that were used more than {1} of expectation\".format(counter, minPlot) )\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "f3e9bde3-06f6-402d-bce1-62b5631e8db0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CORRELATION OF TRACT UNDER-USAGE IN OTHER TRACT'S HOME DISTRICTS vs. being near a boundary\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(tractUse,nearEdge,marker='.' )\n",
    "ax.set(xlabel=\"tract use vs. expectation\", ylabel=\"number of unfilled wedges - max = \"+str(nWedges))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6bb5c12a-a6a4-4cb1-9026-d227bc11c2ea",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.15244490176453734 = VA std dev of TRACT usage.  Here is its weighted histogram\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR tract usage in a histogram\n",
    "n_bins=50\n",
    "avgTractUse = 0.\n",
    "statePop = np.sum(tractPop)\n",
    "for t in range(nTracts):\n",
    "    avgTractUse += tractUse[t] * tractPop[t]/statePop\n",
    "sumVarTractUse = 0.\n",
    "for t in range(nTracts):\n",
    "    sumVarTractUse += (tractUse[t]-avgTractUse)**2 *tractPop[t]/statePop\n",
    "sdTractUse = sumVarTractUse ** 0.5\n",
    "\n",
    "print(sdTractUse,\"=\",STATE,\"std dev of TRACT usage.  Here is its weighted histogram\")\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractUse, bins=n_bins, weights=tractPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "121f9869-3d25-4594-93b3-64a57a95aca8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.15144496140116817 = std dev of PRECINCT usage.  Here is its weighted histogram\n",
      "this is a histogram of PRECINCT usage by precinct for VA\n"
     ]
    },
    {
     "data": {
      "image/png": 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yKS8vT83NzaqoqNDevXtVVFQ07ne+AgAAzBZhgQx3dXXJ6/Wqo6NDlmXpkUceUWVlpTIzMyVJO3fu1MDAgLZs2aKenh6lpaWpqqpKUVFRztd49dVXFRYWpg0bNmhgYECrV6/WkSNHFBoa6swcPXpUBQUFzrtk169fr4MHDzqPh4aG6vjx49qyZYtWrlypiIgI5ebmav/+/c6MZVmqrq7W1q1blZqaqujoaBUVFamoqGhiPykAAIAZ7I6vU2c6rlMHYLbiOnW3xnXqMNtM+nXqAAAAMHMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABgAKIOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAOETfcCAACBWbzr+HQvAcAMxJk6AAAAAxB1AAAABuDpVwDAnDLep69bSrMneSVAcHGmDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABgAKIOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAwQNt0LAABgJlq86/i45lpKsyd5JcD4cKYOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABggICirqSkRH/+53+uqKgoxcbG6tvf/rZ+/etf+83Ytq3du3fL4/EoIiJCq1at0oULF/xmBgcHtW3bNsXExCgyMlLr169XW1ub30xPT4+8Xq8sy5JlWfJ6vbp27ZrfzJUrV7Ru3TpFRkYqJiZGBQUFGhoa8ps5f/68MjIyFBERoYULF2rPnj2ybTuQbQMAAMx4AUVdTU2Ntm7dqrq6OlVXV+uzzz5TVlaW+vv7nZl9+/aprKxMBw8eVH19veLj45WZmam+vj5nprCwUBUVFSovL1dtba2uX7+unJwcDQ8POzO5ublqampSZWWlKisr1dTUJK/X6zw+PDys7Oxs9ff3q7a2VuXl5Tp27Ji2b9/uzPT29iozM1Mej0f19fU6cOCA9u/fr7Kysgn9sAAAAGaqEPsOTltdvXpVsbGxqqmp0V/+5V/Ktm15PB4VFhbqueeek/TFWbm4uDi9/PLL2rx5s3w+nxYsWKC33npLGzdulCS1t7crISFBJ06c0Nq1a3Xp0iUlJSWprq5OaWlpkqS6ujqlp6frww8/VGJiok6ePKmcnBy1trbK4/FIksrLy5WXl6fu7m653W4dPnxYxcXF6urqksvlkiSVlpbqwIEDamtrU0hIyG332NvbK8uy5PP55Ha7J/qjAoCgWbzr+HQvAb+npTR7upcAw423Re7oNXU+n0+SdM8990iSLl++rM7OTmVlZTkzLpdLGRkZOnPmjCSpoaFBN27c8JvxeDxKTk52Zs6ePSvLspygk6Tly5fLsiy/meTkZCfoJGnt2rUaHBxUQ0ODM5ORkeEE3chMe3u7Wlpa7mTrAAAAM8qEo862bRUVFekv/uIvlJycLEnq7OyUJMXFxfnNxsXFOY91dnYqPDxc0dHRY87ExsaO+p6xsbF+Mzd/n+joaIWHh485M/LxyMzNBgcH1dvb63cDAACY6SYcdc8++6z++7//W++8886ox25+WtO27ds+1XnzzK3mgzEz8mzzl62npKTEeXOGZVlKSEgYc90AAAAzwYSibtu2bfrFL36hX/7yl1q0aJFzf3x8vKTRZ8G6u7udM2Tx8fEaGhpST0/PmDNdXV2jvu/Vq1f9Zm7+Pj09Pbpx48aYM93d3ZJGn00cUVxcLJ/P59xaW1vH+EkAAADMDAFFnW3bevbZZ/Wzn/1M//Ef/6ElS5b4Pb5kyRLFx8erurrauW9oaEg1NTVasWKFJCklJUXz5s3zm+no6FBzc7Mzk56eLp/Ppw8++MCZef/99+Xz+fxmmpub1dHR4cxUVVXJ5XIpJSXFmTl9+rTfZU6qqqrk8Xi0ePHiW+7R5XLJ7Xb73QAAAGa6gKJu69at+vGPf6y3335bUVFR6uzsVGdnpwYGBiR98ZRmYWGh9u7dq4qKCjU3NysvL0/z589Xbm6uJMmyLG3atEnbt2/XqVOn1NjYqCeffFIPP/yw1qxZI0launSpHn/8ceXn56uurk51dXXKz89XTk6OEhMTJUlZWVlKSkqS1+tVY2OjTp06pR07dig/P98JsdzcXLlcLuXl5am5uVkVFRXau3evioqKxvXOVwAAgNkiLJDhw4cPS5JWrVrld/+bb76pvLw8SdLOnTs1MDCgLVu2qKenR2lpaaqqqlJUVJQz/+qrryosLEwbNmzQwMCAVq9erSNHjig0NNSZOXr0qAoKCpx3ya5fv14HDx50Hg8NDdXx48e1ZcsWrVy5UhEREcrNzdX+/fudGcuyVF1dra1btyo1NVXR0dEqKipSUVFRINsGAACY8e7oOnVzAdepAzDTcJ26mYXr1GGyTcl16gAAADAzEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABgAKIOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABgAKIOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADhE33AgAAmAsW7zo+rrmW0uxJXglMxZk6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAbgz4QBAHAHxvvnv4DJxpk6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYAAuaQIAMwSXxgBwJzhTBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwQMBRd/r0aa1bt04ej0chISH6+c9/7ve4bdvavXu3PB6PIiIitGrVKl24cMFvZnBwUNu2bVNMTIwiIyO1fv16tbW1+c309PTI6/XKsixZliWv16tr1675zVy5ckXr1q1TZGSkYmJiVFBQoKGhIb+Z8+fPKyMjQxEREVq4cKH27Nkj27YD3TYAAMCMFnDU9ff3a9myZTp48OAtH9+3b5/Kysp08OBB1dfXKz4+XpmZmerr63NmCgsLVVFRofLyctXW1ur69evKycnR8PCwM5Obm6umpiZVVlaqsrJSTU1N8nq9zuPDw8PKzs5Wf3+/amtrVV5ermPHjmn79u3OTG9vrzIzM+XxeFRfX68DBw5o//79KisrC3TbAAAAM1qIfQenrUJCQlRRUaFvf/vbkr44S+fxeFRYWKjnnntO0hdn5eLi4vTyyy9r8+bN8vl8WrBggd566y1t3LhRktTe3q6EhASdOHFCa9eu1aVLl5SUlKS6ujqlpaVJkurq6pSenq4PP/xQiYmJOnnypHJyctTa2iqPxyNJKi8vV15enrq7u+V2u3X48GEVFxerq6tLLpdLklRaWqoDBw6ora1NISEht91jb2+vLMuSz+eT2+2e6I8KAG5r8a7j070EzAAtpdnTvQTMMONtkaC+pu7y5cvq7OxUVlaWc5/L5VJGRobOnDkjSWpoaNCNGzf8Zjwej5KTk52Zs2fPyrIsJ+gkafny5bIsy28mOTnZCTpJWrt2rQYHB9XQ0ODMZGRkOEE3MtPe3q6WlpZb7mFwcFC9vb1+NwAAgJkuqFHX2dkpSYqLi/O7Py4uznmss7NT4eHhio6OHnMmNjZ21NePjY31m7n5+0RHRys8PHzMmZGPR2ZuVlJS4ryOz7IsJSQk3H7jAAAA02xS3v1689Oatm3f9qnOm2duNR+MmZFnm79sPcXFxfL5fM6ttbV1zHUDAADMBEGNuvj4eEmjz4J1d3c7Z8ji4+M1NDSknp6eMWe6urpGff2rV6/6zdz8fXp6enTjxo0xZ7q7uyWNPps4wuVyye12+90AAABmuqBG3ZIlSxQfH6/q6mrnvqGhIdXU1GjFihWSpJSUFM2bN89vpqOjQ83Nzc5Menq6fD6fPvjgA2fm/fffl8/n85tpbm5WR0eHM1NVVSWXy6WUlBRn5vTp036XOamqqpLH49HixYuDuXUAAIBpFXDUXb9+XU1NTWpqapL0xZsjmpqadOXKFYWEhKiwsFB79+5VRUWFmpublZeXp/nz5ys3N1eSZFmWNm3apO3bt+vUqVNqbGzUk08+qYcfflhr1qyRJC1dulSPP/648vPzVVdXp7q6OuXn5ysnJ0eJiYmSpKysLCUlJcnr9aqxsVGnTp3Sjh07lJ+f75xdy83NlcvlUl5enpqbm1VRUaG9e/eqqKhoXO98BQAAmC3CAv2Ec+fO6etf/7rzcVFRkSTpqaee0pEjR7Rz504NDAxoy5Yt6unpUVpamqqqqhQVFeV8zquvvqqwsDBt2LBBAwMDWr16tY4cOaLQ0FBn5ujRoyooKHDeJbt+/Xq/a+OFhobq+PHj2rJli1auXKmIiAjl5uZq//79zoxlWaqurtbWrVuVmpqq6OhoFRUVOWsGAAAwxR1dp24u4Dp1AKYK16mDxHXqMNq0XKcOAAAA04OoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwQNh0LwAAZqvFu46Pa66lNHuSVwIAnKkDAAAwAlEHAABgAKIOAADAAEQdAACAAYg6AAAAAxB1AAAABiDqAAAADEDUAQAAGICLDwMAYLDxXCSbC2SbgTN1AAAABiDqAAAADEDUAQAAGICoAwAAMABRBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAbgL0oAADCDjOcvQEj8FQiMxpk6AAAAAxB1AAAABiDqAAAADEDUAQAAGICoAwAAMADvfgUAYBYa77tkMXdwpg4AAMAARB0AAIABiDoAAAADEHUAAAAGIOoAAAAMQNQBAAAYgKgDAAAwAFEHAABgAKIOAADAAEQdAACAAfgzYQAwyfhzTgCmAlEHALdAiAGYbYg6AHMKsQbAVEQdYKjxxktLafYkrwQAMBV4owQAAIABiDoAAAAD8PQrAAAYF17WMbNxpg4AAMAARB0AAIABiDoAAAADEHUAAAAG4I0SAGY0XpgNAOND1AEwAn8pAsBcR9QBADDH8Y8iM/CaOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAN0oAMwQvVAYA3AnO1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABePcrAAAIqvG+m7+lNHuSVzK3EHUAAGBGIxLHh6gDEFQcfAFgevCaOgAAAANwpg4AAEyLYP8lnWA/UzDbnnmYE1F36NAhvfLKK+ro6NCf/umf6rXXXtNjjz023csCAADTwNQ/y2h81L377rsqLCzUoUOHtHLlSv3whz/UN7/5TV28eFF/9Ed/NN3LA+YsUw+qADBdjH9NXVlZmTZt2qSnn35aS5cu1WuvvaaEhAQdPnx4upcGAAAQNEafqRsaGlJDQ4N27drld39WVpbOnDlzy88ZHBzU4OCg87HP55Mk9fb2Tt5CAUmfD346Ld832P9tT9c+AGC6THYjjHx927bHnDM66j766CMNDw8rLi7O7/64uDh1dnbe8nNKSkr00ksvjbo/ISFhUtYITDfrteleAQDMblN1HO3r65NlWV/6uNFRNyIkJMTvY9u2R903ori4WEVFRc7Hn3/+uT755BPde++9X/o5d6q3t1cJCQlqbW2V2+2elO8xk83l/c/lvUvsn/3P3f3P5b1L7D/Q/du2rb6+Pnk8njHnjI66mJgYhYaGjjor193dPers3QiXyyWXy+V33x/+4R9O1hL9uN3uOfkf94i5vP+5vHeJ/bP/ubv/ubx3if0Hsv+xztCNMPqNEuHh4UpJSVF1dbXf/dXV1VqxYsU0rQoAACD4jD5TJ0lFRUXyer1KTU1Venq6fvSjH+nKlSt65plnpntpAAAAQWN81G3cuFEff/yx9uzZo46ODiUnJ+vEiRO6//77p3tpDpfLpRdffHHU075zxVze/1zeu8T+2f/c3f9c3rvE/idr/yH27d4fCwAAgBnP6NfUAQAAzBVEHQAAgAGIOgAAAAMQdQAAAAYg6qbIoUOHtGTJEt19991KSUnRe++9N+Z8TU2NUlJSdPfdd+uBBx7Qv/7rv07RSoMvkL3/7Gc/U2ZmphYsWCC326309HT9+7//+xSuNvgC/d2P+M///E+FhYXpq1/96uQucJIFuv/BwUG98MILuv/+++VyufTHf/zH+rd/+7cpWm3wBbr/o0ePatmyZZo/f77uu+8+/c3f/I0+/vjjKVpt8Jw+fVrr1q2Tx+NRSEiIfv7zn9/2c0w67gW6f9OOfRP5/Y+Y7ce+iew9WMc9om4KvPvuuyosLNQLL7ygxsZGPfbYY/rmN7+pK1eu3HL+8uXL+ta3vqXHHntMjY2Nev7551VQUKBjx45N8crvXKB7P336tDIzM3XixAk1NDTo61//utatW6fGxsYpXnlwBLr/ET6fT9/5zne0evXqKVrp5JjI/jds2KBTp07pjTfe0K9//Wu98847euihh6Zw1cET6P5ra2v1ne98R5s2bdKFCxf0k5/8RPX19Xr66aeneOV3rr+/X8uWLdPBgwfHNW/ScU8KfP+mHfsC3f8IE459E9l70I57Nibdo48+aj/zzDN+9z300EP2rl27bjm/c+dO+6GHHvK7b/Pmzfby5csnbY2TJdC930pSUpL90ksvBXtpU2Ki+9+4caP9z//8z/aLL75oL1u2bBJXOLkC3f/Jkydty7Lsjz/+eCqWN+kC3f8rr7xiP/DAA373vf766/aiRYsmbY1TQZJdUVEx5oxJx72bjWf/tzKbj32/L5D9m3LsGzGevQfzuMeZukk2NDSkhoYGZWVl+d2flZWlM2fO3PJzzp49O2p+7dq1OnfunG7cuDFpaw22iez9Zp9//rn6+vp0zz33TMYSJ9VE9//mm2/qt7/9rV588cXJXuKkmsj+f/GLXyg1NVX79u3TwoUL9ZWvfEU7duzQwMDAVCw5qCay/xUrVqitrU0nTpyQbdvq6urST3/6U2VnZ0/FkqeVKce9YJnNx76JMuXYF6hgHveM/4sS0+2jjz7S8PCw4uLi/O6Pi4tTZ2fnLT+ns7PzlvOfffaZPvroI913332Ttt5gmsjeb/b9739f/f392rBhw2QscVJNZP+/+c1vtGvXLr333nsKC5vd/3tOZP+/+93vVFtbq7vvvlsVFRX66KOPtGXLFn3yySez7nV1E9n/ihUrdPToUW3cuFH/93//p88++0zr16/XgQMHpmLJ08qU416wzOZj30SYdOwLVDCPe5ypmyIhISF+H9u2Peq+283f6v7ZINC9j3jnnXe0e/duvfvuu4qNjZ2s5U268e5/eHhYubm5eumll/SVr3xlqpY36QL5/X/++ecKCQnR0aNH9eijj+pb3/qWysrKdOTIkVl5tk4KbP8XL15UQUGBvvvd76qhoUGVlZW6fPnynPlb1SYd9+6EKce+8TL12DdewTzuza0cngYxMTEKDQ0d9S/z7u7uUf8qHREfH3/L+bCwMN17772TttZgm8jeR7z77rvatGmTfvKTn2jNmjWTucxJE+j++/r6dO7cOTU2NurZZ5+V9MX/7LZtKywsTFVVVfrGN74xJWsPhon8/u+77z4tXLhQlmU59y1dulS2bautrU0PPvjgpK45mCay/5KSEq1cuVL/9E//JEl65JFHFBkZqccee0zf+973jD5bZcpx706ZcOwLlGnHvkAF87jHmbpJFh4erpSUFFVXV/vdX11drRUrVtzyc9LT00fNV1VVKTU1VfPmzZu0tQbbRPYuffGv1Ly8PL399tuz+rVEge7f7Xbr/Pnzampqcm7PPPOMEhMT1dTUpLS0tKlaelBM5Pe/cuVKtbe36/r16859//M//6O77rpLixYtmtT1BttE9v/pp5/qrrv8D8uhoaGS/v9ZK1OZcty7E6Yc+wJl2rEvUEE97t3xWy1wW+Xl5fa8efPsN954w7548aJdWFhoR0ZG2i0tLbZt2/auXbtsr9frzP/ud7+z58+fb//jP/6jffHiRfuNN96w582bZ//0pz+dri1MWKB7f/vtt+2wsDD7Bz/4gd3R0eHcrl27Nl1buCOB7v9ms/0dYIHuv6+vz160aJH913/91/aFCxfsmpoa+8EHH7Sffvrp6drCHQl0/2+++aYdFhZmHzp0yP7tb39r19bW2qmpqfajjz46XVuYsL6+PruxsdFubGy0JdllZWV2Y2Oj/b//+7+2bZt93LPtwPdv2rEv0P3fbDYf+wLdezCPe0TdFPnBD35g33///XZ4eLj9ta99za6pqXEee+qpp+yMjAy/+V/96lf2n/3Zn9nh4eH24sWL7cOHD0/xioMnkL1nZGTYkkbdnnrqqalfeJAE+rv/fbP5wDYi0P1funTJXrNmjR0REWEvWrTILioqsj/99NMpXnXwBLr/119/3U5KSrIjIiLs++67z37iiSfstra2KV71nfvlL3855v/Lph/3At2/ace+ifz+f99sPvZNZO/BOu6F2Lbh5/QBAADmAF5TBwAAYACiDgAAwABEHQAAgAGIOgAAAAMQdQAAAAYg6gAAAAxA1AEAABiAqAMAADAAUQcAAGAAog4AAMAARB0AAIABiDoAAAAD/D/XD1YmJ1/sjgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR precinct usage in a histogram  \n",
    "# 8/5/23 - NOTE THAT BOTH TRACT AND PRECINCT USAGE DISTRO'S ARE V SIMILAR FOR 14- VS. 11-DISTRICT MAPS\n",
    "n_bins=50\n",
    "avgPrecinctUse = 0.\n",
    "stateVTDPop = np.sum(vtdPop)\n",
    "for p in range(nPrecincts):\n",
    "    avgPrecinctUse += precinctUse[p] * vtdPop[p]/stateVTDPop\n",
    "sumVarPrecinctUse = 0.\n",
    "for p in range(nPrecincts):\n",
    "    sumVarPrecinctUse += (precinctUse[p]-avgPrecinctUse)**2 *vtdPop[p]/stateVTDPop\n",
    "sdPrecinctUse = sumVarPrecinctUse ** 0.5\n",
    "\n",
    "print(sdPrecinctUse,\"= std dev of PRECINCT usage.  Here is its weighted histogram\")\n",
    "print(\"this is a histogram of PRECINCT usage by precinct for\",STATE)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(precinctUse, bins=n_bins, weights=vtdPop)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f6f03dcb-c722-4789-b47f-fb7aa3be97bc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here's a look at numerical stability - number of loops, avg =  7.8285\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "avgTLC = 0.\n",
    "usedTracts = 0.\n",
    "for t in range (nTracts):\n",
    "    if(tractLoopCounter[t] > 0):\n",
    "        avgTLC += tractLoopCounter[t]\n",
    "        usedTracts +=1.\n",
    "avgTLC = round(avgTLC / usedTracts, 4)\n",
    "print(\"here's a look at numerical stability - number of loops, avg = \",avgTLC)\n",
    "n_bins=20     \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(tractLoopCounter, bins=n_bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "974631b2-10ef-4847-af2e-a1e26b6fa768",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district pct GOP by tract\n",
      "statewide vote is off by 0.00065 0.44911 HD avg vs true 0.44845\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR HOME DISTRICT red-blue lean in a histogram  and check the statewide vote vs. HD average\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district pct GOP by tract\") \n",
    "print(\"statewide vote is off by\",round((stateGOP2-stateGOP),5),round(stateGOP2,5),\"HD avg vs true\",round(stateGOP,5))\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDvGOP, bins=n_bins,weights=HDweight)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "720d9eb5-11e8-45f7-b402-a0048e9ddb99",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculated statewide Hispanic pct was 0.08715, should have been 0.09107\n",
      "this is a histogram of home-district VAP pct Hispanic by tract\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR home district pct Hispanic in a histogram\n",
    "print(\"calculated statewide Hispanic pct was {0}, should have been {1}\"\n",
    "      .format(round(stateHisp2,5), round(np.sum(tractHisp)/np.sum(tractVAP),5) ) )\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district VAP pct Hispanic by tract\")        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDvHisp, bins=[0.1,0.15,0.2,0.25,0.3,0.35,0.4,0.45,0.5,0.55,0.6,0.65,0.7,0.75,0.8,0.85,0.9,0.95,1.0],\n",
    "        weights=HDweight)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "1ab7704f-a226-45a9-98a6-d0684522c1eb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a bar plot of seats by VAP pct Hispanic for VA\n"
     ]
    },
    {
     "data": {
      "image/png": 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Zo0eP9kVGAAAQoBxfRyUkJEQzZszQ2LFjlZeXp/Lycl1yySVKTEz0RT4AABDAHBeVCuedd54SEhIkSS6Xy2uBAAAAKtTogm/Tpk1Tu3btFB4ervDwcLVr107vvfeet7MBAIAA53hF5dlnn9Ubb7yhwYMHKz09XZK0cuVKDRs2TNu3b9eLL77o9ZAAACAwOS4qOTk5mjp1qgYMGOAe69evn9q3b6/BgwdTVAAAgNc4PvRTVlamtLS0SuOpqak6ceKEV0IBAABINSgqd955p3JyciqNT5kyRXfccYdXQgEAAEjVPPSTmZnp/rfL5dJ7772nhQsX6rLLLpMkff/99yooKOCCbwAAwKuqVVTy8vI8tlNTUyVJW7ZskfT79/w0bdpUGzdu9HI8AAAQyKpVVBYtWuTrHAAAAJXU6DoqAAAAtcHxx5OPHTumSZMmadGiRSosLFR5ebnH/WvXrq32c2VnZ+vTTz/Vv//9b0VERKhz58565ZVXdOGFFzqNBQAAzkCOi8p9992n3Nxc3XLLLerYseNpXT5/yZIleuyxx9ShQwedOHFCo0aNUs+ePZWfn68GDRrU+HkBAMCZwXFR+fLLLzV//nx16dLltF98wYIFHtsffPCBzjnnHK1Zs0ZXXnllpf1LS0tVWlrq3i4uLj7tDAAAwF6Oz1GJjY1VZGSkL7Lo4MGDkqTGjRtXeX92draio6Pdt7i4OJ/kAAAAdnBcVF577TUNHz5cO3bs8GoQY4wyMzN1+eWXq127dlXuM3LkSB08eNB9Kygo8GoGAABgF8eHftLS0nTs2DElJCSofv36CgkJ8bi/qKioRkEGDRqk9evX67vvvjvpPmFhYQoLC6vR8wMAgLrHcVEZMGCA/u///k8vv/yymjVrdlon01YYPHiwPv/8cy1dulQtWrQ47ecDAABnBsdFZcWKFVq5cqWSk5NP+8WNMRo8eLDmzZunxYsXq3Xr1qf9nAAA4MzhuKgkJSXp6NGjXnnxxx57TDNnztQ//vEPRUZGau/evZKk6OhoRUREeOU1AABA3eX4ZNpx48bpiSee0OLFi7V//34VFxd73JzIycnRwYMHlZGRoZiYGPdt9uzZTmMBAIAzkOMVlV69ekmSrrrqKo9xY4xcLpfKysqq/VzGGKcvDwAAAojjosIXFAIAgNriuKh07drVFzkAAAAqcVxUli5desr7q7r0PQAAQE04LioZGRmVxv54LRUn56gAAACciuNP/fz6668et8LCQi1YsEAdOnTQwoULfZERAAAEKMcrKtHR0ZXGevToobCwMA0bNkxr1qzxSjAAAADHKyon07RpU23atMlbTwcAAOB8RWX9+vUe28YY7dmzR+PGjfPKZfUBAAAqOC4qKSkpcrlclS7Wdtlll+n999/3WjDYodWIL/0d4aS2j+vr7wgAAB9zXFS2bdvmsR0UFKSmTZsqPDzca6EAAACkGhSV+Ph4X+QAAACoxHFRkaRvv/1W3377rQoLC1VeXu5xH4d/AACAtzguKllZWRo7dqzS0tIUExPjcbE3AAAAb3JcVN555x1Nnz5dd911ly/yAAAAuDm+jsrx48fVuXNnX2QBAADw4LioPPDAA5o5c6YvsgAAAHhwfOjn2LFjmjJlir755hu1b99eISEhHve//vrrXgsHAAACW42uTJuSkiJJ+umnnzzu48RaAADgTY6LyqJFi3yRAwAAoBKvfSkhAACAt1FUAACAtSgqAADAWhQVAABgLYoKAACwFkUFAABYi6ICAACsRVEBAADWoqgAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALCW429Pxpmr1Ygv/R0BAAAPrKgAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALAWRQUAAFiLogIAAKxFUQEAANaiqAAAAGtRVAAAgLUoKgAAwFoUFQAAYC2KCgAAsBZFBQAAWIuiAgAArEVRAQAA1qKoAAAAa1FUAACAtSgqAADAWhQVAABgLYoKAACwFkUFAABYi6ICAACsRVEBAADWoqgAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALAWRQUAAFiLogIAAKxFUQEAANbya1FZunSprrvuOjVv3lwul0ufffaZP+MAAADL+LWoHD58WMnJyZo8ebI/YwAAAEsF+/PFe/furd69e/szAgAAsJhfi4pTpaWlKi0tdW8XFxf7MQ0AAPC1OnUybXZ2tqKjo923uLg4f0cCAAA+VKeKysiRI3Xw4EH3raCgwN+RAACAD9WpQz9hYWEKCwvzdwwAAFBL6tSKCgAACCx+XVE5dOiQNm/e7N7etm2b1q1bp8aNG6tly5Z+TAYAAGzg16KyevVqdevWzb2dmZkpSRo4cKCmT5/up1QAAMAWfi0qGRkZMsb4MwIAALAY56gAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALAWRQUAAFiLogIAAKxFUQEAANaiqAAAAGtRVAAAgLUoKgAAwFoUFQAAYC2KCgAAsBZFBQAAWIuiAgAArEVRAQAA1qKoAAAAa1FUAACAtSgqAADAWhQVAABgLYoKAACwFkUFAABYi6ICAACsRVEBAADWoqgAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALAWRQUAAFiLogIAAKxFUQEAANaiqAAAAGtRVAAAgLUoKgAAwFoUFQAAYC2KCgAAsBZFBQAAWIuiAgAArEVRAQAA1qKoAAAAa1FUAACAtSgqAADAWhQVAABgLYoKAACwFkUFAABYi6ICAACsRVEBAADWoqgAAABrBfs7AFBTrUZ86fXn3D6ur9efEwBQc6yoAAAAa1FUAACAtSgqAADAWhQVAABgLYoKAACwFkUFAABYi6ICAACsRVEBAADWoqgAAABrUVQAAIC1KCoAAMBaFBUAAGAtigoAALAWRQUAAFiLogIAAKxFUQEAANbye1F5++231bp1a4WHhys1NVXLli3zdyQAAGAJvxaV2bNna+jQoRo1apTy8vJ0xRVXqHfv3tq5c6c/YwEAAEv4tai8/vrruv/++/XAAw+oTZs2mjBhguLi4pSTk+PPWAAAwBLB/nrh48ePa82aNRoxYoTHeM+ePbVixYoqH1NaWqrS0lL39sGDByVJxcXFPslYXnrEJ88Le/nqdwkA8F8Vf2uNMX+6r9+Kyr59+1RWVqZmzZp5jDdr1kx79+6t8jHZ2dnKysqqNB4XF+eTjAg80RP8nQAAAkdJSYmio6NPuY/fikoFl8vlsW2MqTRWYeTIkcrMzHRvl5eXq6ioSE2aNDnpY3yluLhYcXFxKigoUFRUVK2+9pmOufUd5tZ3mFvfYF59x59za4xRSUmJmjdv/qf7+q2onH322apXr16l1ZPCwsJKqywVwsLCFBYW5jHWsGFDX0WslqioKP7j8RHm1neYW99hbn2DefUdf83tn62kVPDbybShoaFKTU1Vbm6ux3hubq46d+7sp1QAAMAmfj30k5mZqbvuuktpaWlKT0/XlClTtHPnTj3yyCP+jAUAACzh16LSv39/7d+/X2PHjtWePXvUrl07zZ8/X/Hx8f6MVS1hYWEaM2ZMpUNROH3Mre8wt77D3PoG8+o7dWVuXaY6nw0CAADwA79fQh8AAOBkKCoAAMBaFBUAAGAtigoAALAWReUU3n77bbVu3Vrh4eFKTU3VsmXLTrn/kiVLlJqaqvDwcCUkJOidd96ppaR1j5O5/fTTT9WjRw81bdpUUVFRSk9P19dff12LaesWp7+3FZYvX67g4GClpKT4NmAd5XReS0tLNWrUKMXHxyssLEznnXee3n///VpKW7c4ndsZM2YoOTlZ9evXV0xMjO69917t37+/ltLWDUuXLtV1112n5s2by+Vy6bPPPvvTx1j7HmZQpVmzZpmQkBAzdepUk5+fb4YMGWIaNGhgduzYUeX+W7duNfXr1zdDhgwx+fn5ZurUqSYkJMR88skntZzcfk7ndsiQIeaVV14xq1atMj///LMZOXKkCQkJMWvXrq3l5PZzOrcVDhw4YBISEkzPnj1NcnJy7YStQ2oyr/369TOdOnUyubm5Ztu2beaHH34wy5cvr8XUdYPTuV22bJkJCgoyb775ptm6datZtmyZueiii8wNN9xQy8ntNn/+fDNq1Cgzd+5cI8nMmzfvlPvb/B5GUTmJjh07mkceecRjLCkpyYwYMaLK/Z9++mmTlJTkMfbwww+byy67zGcZ6yqnc1uVtm3bmqysLG9Hq/NqOrf9+/c3o0ePNmPGjKGoVMHpvH711VcmOjra7N+/vzbi1WlO5/bVV181CQkJHmMTJ040LVq08FnGuq46RcXm9zAO/VTh+PHjWrNmjXr27Okx3rNnT61YsaLKx6xcubLS/tdcc41Wr16t3377zWdZ65qazO3/Ki8vV0lJiRo3buyLiHVWTef2gw8+0JYtWzRmzBhfR6yTajKvn3/+udLS0jR+/HjFxsbqggsu0JNPPqmjR4/WRuQ6oyZz27lzZ+3atUvz58+XMUa//PKLPvnkE/Xt27c2Ip+xbH4P8/u3J9to3759Kisrq/TliM2aNav0JYoV9u7dW+X+J06c0L59+xQTE+OzvHVJTeb2f7322ms6fPiwbr31Vl9ErLNqMrf/+c9/NGLECC1btkzBwfw5qEpN5nXr1q367rvvFB4ernnz5mnfvn169NFHVVRUxHkqf1CTue3cubNmzJih/v3769ixYzpx4oT69eunSZMm1UbkM5bN72GsqJyCy+Xy2DbGVBr7s/2rGofzua3w97//Xc8//7xmz56tc845x1fx6rTqzm1ZWZluv/12ZWVl6YILLqiteHWWk9/Z8vJyuVwuzZgxQx07dlSfPn30+uuva/r06ayqVMHJ3Obn5+vxxx/Xc889pzVr1mjBggXatm0b3xHnBba+h/G/UFU4++yzVa9evUqNvrCwsFLjrHDuuedWuX9wcLCaNGnis6x1TU3mtsLs2bN1//33a86cObr66qt9GbNOcjq3JSUlWr16tfLy8jRo0CBJv7/BGmMUHByshQsXqnv37rWS3WY1+Z2NiYlRbGysx9fYt2nTRsYY7dq1S4mJiT7NXFfUZG6zs7PVpUsXPfXUU5Kk9u3bq0GDBrriiiv04osvsnpdQza/h7GiUoXQ0FClpqYqNzfXYzw3N1edO3eu8jHp6emV9l+4cKHS0tIUEhLis6x1TU3mVvp9JeWee+7RzJkzORZ9Ek7nNioqShs2bNC6devct0ceeUQXXnih1q1bp06dOtVWdKvV5He2S5cu2r17tw4dOuQe+/nnnxUUFKQWLVr4NG9dUpO5PXLkiIKCPN+66tWrJ+m/KwBwzur3MD+dxGu9io/MTZs2zeTn55uhQ4eaBg0amO3btxtjjBkxYoS566673PtXfLRr2LBhJj8/30ybNs2aj3bZxunczpw50wQHB5u33nrL7Nmzx307cOCAv34Eazmd2//Fp36q5nReS0pKTIsWLcwtt9xiNm7caJYsWWISExPNAw884K8fwVpO5/aDDz4wwcHB5u233zZbtmwx3333nUlLSzMdO3b0149gpZKSEpOXl2fy8vKMJPP666+bvLw898e+69J7GEXlFN566y0THx9vQkNDzaWXXmqWLFnivm/gwIGma9euHvsvXrzYXHLJJSY0NNS0atXK5OTk1HLiusPJ3Hbt2tVIqnQbOHBg7QevA5z+3v4RReXknM7rv/71L3P11VebiIgI06JFC5OZmWmOHDlSy6nrBqdzO3HiRNO2bVsTERFhYmJizB133GF27dpVy6nttmjRolP+3axL72EuY1grAwAAduIcFQAAYC2KCgAAsBZFBQAAWIuiAgAArEVRAQAA1qKoAAAAa1FUAACAtSgqAADAWhQVAFZwuVz67LPP/B3DQ0ZGhoYOHervGEBAo6gAcGzx4sVyuVw6cOBAjfdr1aqVJkyY4N7es2ePevfu7d2gp+nTTz/VCy+84O8YQEAL9ncAAJB+/5p52zRu3NjfEYCAx4oKEIAyMjI0aNAgDRo0SA0bNlSTJk00evRo/fGrv0pLS/X0008rLi5OYWFhSkxM1LRp07R9+3Z169ZNktSoUSO5XC7dc889p53pj4d+jh8/rkGDBikmJkbh4eFq1aqVsrOzPfbNyclR7969FRERodatW2vOnDkezzd8+HBdcMEFql+/vhISEvTss8/qt99+c9///PPPKyUlRR999JFatWql6Oho3XbbbSopKfGYpz8e+jnZnADwHVZUgAD14Ycf6v7779cPP/yg1atX66GHHlJ8fLwefPBBSdLdd9+tlStXauLEiUpOTta2bdu0b98+xcXFae7cubr55pu1adMmRUVFKSIiwqvZJk6cqM8//1wff/yxWrZsqYKCAhUUFHjs8+yzz2rcuHF688039dFHH2nAgAFq166d2rRpI0mKjIzU9OnT1bx5c23YsEEPPvigIiMj9fTTT7ufY8uWLfrss8/0xRdf6Ndff9Wtt96qcePG6aWXXqoy18nmBIAP+fnbmwH4QdeuXU2bNm1MeXm5e2z48OGmTZs2xhhjNm3aZCSZ3NzcKh9f8RXyv/766ylfp2K/Bg0aVLq5XC7zxhtvuPeVZObNm2eMMWbw4MGme/fuHvn+SJJ55JFHPMY6depk/vKXv5w0y/jx401qaqp7e8yYMaZ+/fqmuLjYPfbUU0+ZTp06ube7du1qhgwZYoz58zkB4BusqAAB6rLLLpPL5XJvp6en67XXXlNZWZnWrVunevXqqWvXrl55rWXLlikyMtJjLCMj46T733PPPerRo4cuvPBC9erVS9dee6169uzpsU96enql7XXr1rm3P/nkE02YMEGbN2/WoUOHdOLECUVFRXk8plWrVh65YmJiVFhYWGUmb88JgOrhHBUAlXj7UE7r1q11/vnne9yCg0/+/0mXXnqptm3bphdeeEFHjx7VrbfeqltuueVPX6eieH3//fe67bbb1Lt3b33xxRfKy8vTqFGjdPz4cY/9Q0JCKj2+vLy8yuf29pwAqB6KChCgvv/++0rbiYmJqlevni6++GKVl5dryZIlVT42NDRUklRWVuazfFFRUerfv7+mTp2q2bNna+7cuSoqKjpl/qSkJEnS8uXLFR8fr1GjRiktLU2JiYnasWPHaeX5szkB4Bsc+gECVEFBgTIzM/Xwww9r7dq1mjRpkl577TVJvx8SGThwoO677z73iaM7duxQYWGhbr31VsXHx8vlcumLL75Qnz59FBERobPOOstr2d544w3FxMQoJSVFQUFBmjNnjs4991w1bNjQvc+cOXOUlpamyy+/XDNmzNCqVavcn8A5//zztXPnTs2aNUsdOnTQl19+qXnz5p1Wpj+bEwC+wYoKEKDuvvtuHT16VB07dtRjjz2mwYMH66GHHnLfn5OTo1tuuUWPPvqokpKS9OCDD+rw4cOSpNjYWGVlZWnEiBFq1qyZBg0a5NVsZ511ll555RWlpaWpQ4cO2r59u+bPn6+goP/+ycrKytKsWbPUvn17ffjhh5oxY4batm0rSbr++us1bNgwDRo0SCkpKVqxYoWeffbZ0851qjkB4BsuY/5w4QQAASEjI0MpKSkeV4atS1wul+bNm6cbbrjB31EA+BgrKgAAwFoUFQAAYC0O/QAAAGuxogIAAKxFUQEAANaiqAAAAGtRVAAAgLUoKgAAwFoUFQAAYC2KCgAAsBZFBQAAWOv/AREH4ggKVQgiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ALTERNATE VIEW OF HISPANIC VOTE: HOW MANY DISTRICTS PER 10pct BIN of PCT HISPANIC VOTE?\n",
    "n_bins = 20\n",
    "HispSeats = [0.]*n_bins\n",
    "binMid = [0.]*n_bins\n",
    "for b in range(n_bins):\n",
    "    binMid[b]= float(b)/n_bins + 0.5/n_bins  #centering each bin\n",
    "for t in range(nTracts) :\n",
    "    b = int(HDvHisp[t]*n_bins)\n",
    "    HispSeats[b] += HDweight[t]*nDistricts  #multiply by nDistricts to get number of expected seats\n",
    "\n",
    "print(\"this is a bar plot of seats by VAP pct Hispanic for\",STATE)        \n",
    "fig, ax = plt.subplots()\n",
    "plt.bar(binMid,HispSeats,width=0.09 )\n",
    "#plt.scatter(binMid,HispSeats )\n",
    "ax.set(xlabel=\"pct Hispanic\", ylabel=\"number of seats\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "b1e9c437-ddf7-4202-aff0-19f338a5d013",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Black candidates would expect to win 4.115 VA seats out of 11\n",
      "Using simple Alabama-style of Blacks voting 0.9 Dem and whites voting 0.8 GOP\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Where in the state do we see opportunity home districts?  #NEW FORMULATION based on ALABAMA\n",
    "isOppor = [0]*nTracts #will track whether this is an opportunity district\n",
    "blackFracSeats = 0.\n",
    "blackPctDem = 0.9  #fraction of Black voters who are Democrats (est'd from Chen / Stephanopoulos)\n",
    "whitePctGOP = 0.8   #fraction of White voters who are Republican  (\"  \")\n",
    "#minBlack1 = 0.30\n",
    "#minBlack2 = 0.50\n",
    "for t in range(nTracts):\n",
    "    pctWhiteDem = (1-whitePctGOP)*(1-HDvBlack[t])  #this is the fraction of voters who are white Democrats\n",
    "    pctBlackDem = blackPctDem * HDvBlack[t]  #fraction of voters who are black Democrats\n",
    "    if tractPop[t] > minTractPop and HDvGOP[t] < 0.5 :  #Dems would win this Home District\n",
    "        if pctBlackDem > pctWhiteDem : #Blacks would win the primary\n",
    "            isOppor[t] = 1\n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='blue' )\n",
    "            blackFracSeats += HDweight[t]\n",
    "        else :  #the White Dem candidate would win the election          \n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='gray' )\n",
    "\n",
    "print(\"Black candidates would expect to win\",round(blackFracSeats*nDistricts,3),STATE,\"seats out of\",nDistricts)\n",
    "print(\"Using simple Alabama-style of Blacks voting\",blackPctDem,\"Dem and whites voting\",whitePctGOP,\"GOP\")\n",
    "x,y = wholeMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "c5125128-e4bb-4337-bc5e-3f48d7cf404f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here's the VA map with Hisp+Black greater than  0.4 or even 0.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Where in the state do we see Black+Hispanic heavy home districts?\n",
    "minMinor = 0.40 \n",
    "minMinor2 = 0.50\n",
    "print(\"Here's the\",STATE,\"map with Hisp+Black greater than \",minMinor,\"or even\",minMinor2)\n",
    "for t in range(nTracts):\n",
    "    if ((HDvBlack[t] + HDvHisp[t]) > minMinor and tractPop[t] > minTractPop):\n",
    "        if (HDvBlack[t] + HDvHisp[t]) > minMinor2 :\n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='blue' )\n",
    "        else :            \n",
    "            plt.scatter(tractCPx[t],tractCPy[t],marker='.',color='gray' )\n",
    "\n",
    "x,y = tractMAP.exterior.xy\n",
    "plt.plot(x,y,c=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "58119ef8-13ef-4135-9843-6518025dda07",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district population by tract; avg =  784666.7272727273\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# LET'S VISUALIZE OUR HOME DISTRICT population in a histogram\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district population by tract; avg = \",np.sum(tractPop)/nDistricts)        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "a = avgDistrictPop\n",
    "ax.hist(HDvPop, bins=[0.9*a,0.92*a,0.95*a,0.99*a,1.0*a,1.01*a,1.05*a,1.1*a])   #n_bins\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "1f9101bd-108a-48cb-bee5-3f4e04c18132",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this is a histogram of home-district area by tract\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# more HOME DISTRICT STATS in a histogram\n",
    "n_bins=50\n",
    "print(\"this is a histogram of home-district area by tract\")        \n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "# We can set the number of bins with the *bins* keyword argument.\n",
    "ax.hist(HDarea, bins=n_bins)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "d8167a80-2b91-4adc-ab34-9e010838213d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of HD area to red-blue lean?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(HDarea,HDvGOP,marker='.' )\n",
    "ax.set(xlabel=\"tract area\", ylabel=\"home district pct GOP\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "cf95cc7c-e58a-4174-94f6-b6d4c7ccb0ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of tract usage to red-blue lean?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(HDvGOP,tractUse, marker='.' )\n",
    "ax.set(xlabel=\"home district pct GOP\", ylabel=\"tractUse\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "617384b8-1e0b-45a7-ae09-babe8dd9d429",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the correlation of tract usage to tract population?\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(tractPop,tractUse, marker='.' )\n",
    "ax.set(xlabel=\"Census tract population\", ylabel=\"tractUse\")\n",
    "ax.set_xlim(left=0,right=10000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "91f163ab-6b94-47ee-bd29-be3e751fe2b4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# UPDATED VOTES-SEATS CURVE (from votes2seats.ipynb 1/15/22)\n",
    "# LET'S REWORK OUR VOTES - SEATS CALCULATIONS\n",
    "# FIRST, LET'S DO THE BASIC VOTES-TO-SEATS, no fractional seats\n",
    "# INPUTS ARE HDvGOP[nTracts] and HDweight[nTracts]\n",
    "# HDvGOP is the redness lean of each Census tract's Home District\n",
    "# HDweight is the population of this Census tract relative to the state population\n",
    "# stateGOP is the statewide fraction of GOP vote vs. GOP + Dem vote\n",
    "# KEY EQUATION:\n",
    "# expected Seats at a given vote V = sum(HDweight) for tracts with HDvGOP > 0.5 + (V - stateGOP)\n",
    "# for easy calculation, create ~1000 bins, each bin containing HD's in a dV vote window\n",
    "nBins = 1000\n",
    "dV = 1./nBins\n",
    "binWeight = [0.]*nBins\n",
    "\n",
    "for t in range(nTracts):\n",
    "    binNo = int(HDvGOP[t]*nBins)   #which vote bin does this tract's vote go into for the expected statewide vote?\n",
    "    binWeight[binNo] += HDweight[t]\n",
    "    \n",
    "binVote = [0.]*nBins  #this will store the statewide vote for this bin\n",
    "for b in range(nBins) :\n",
    "    binVote[b] = b*dV\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, binWeight, marker='.',linestyle=\"none\")\n",
    "ax.set(xlabel=\"district pct GOP\", ylabel=\"bin weight\")\n",
    "plt.show()   #this should resemble above histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "85608d3f-c3bd-4d91-9378-16270ceeb9b6",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with votes-to-seats, let's compute the S(V) curve with no fractional-seat smearing\n",
    "cumVote = [0.]*nBins\n",
    "for b in range(nBins) :\n",
    "    cumVote[nBins-b-1] = np.sum(binWeight[:(b+1)])  #cumulative weight of all Home Districts below vote b*dV\n",
    "    # print(\"bin, bin vote, cumVote for this bin\",b,b*dV,cumVote[b] )\n",
    "    \n",
    "cumSeats = [0.]*nBins  #this will sum the seats earned for a given statewide vote\n",
    "stateVoteBin = int( (stateGOP+0.5*dV)*nBins )   #which bin (out of 1/dV) holds the statewide total vote?\n",
    "for b in range(nBins) :\n",
    "    bb = int( max(0,min(nBins-1,nBins/2 + b-stateVoteBin)) )\n",
    "    cumSeats[b] = 1. - cumVote[bb]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, cumSeats, marker='.',linestyle=\"none\")\n",
    "ax.set(xlabel=\"statewide vote, nBins =\"+str(nBins)+\",\"+str(STATE), ylabel=\"GOP seats won (no fractl smearing)\")\n",
    "RANGE = [0.1, 0.9]\n",
    "fifty50 = [0.5, 0.5]\n",
    "expected = [stateGOP, stateGOP]\n",
    "plt.plot(RANGE,fifty50)\n",
    "plt.plot(fifty50,RANGE)\n",
    "plt.plot(expected,RANGE, linestyle=\"--\",color='red')\n",
    "\n",
    "#LET'S ALSO crudely ESTIMATE RESPONSIVENESS near the STATEWIDE VOTE, with a pseudonormal weighting and lst-sq fit\n",
    "stateSigma = 0.03  #User-adjustable, this is the uncertainty in the statewide vote from election to election\n",
    "usedBins = int(stateSigma/dV)\n",
    "nFitPoints = 6*usedBins\n",
    "voteData = [0.]*nFitPoints\n",
    "seatData = [0.]*nFitPoints\n",
    "counter = 0\n",
    "for b in range(nBins):\n",
    "    if ( abs(b-stateVoteBin) <= 2*usedBins ):  #include this S-V pair in our line fit\n",
    "        voteData[counter]=binVote[b]\n",
    "        seatData[counter]=cumSeats[b]\n",
    "        counter += 1\n",
    "        # print(b,counter)\n",
    "        if ( abs(b-stateVoteBin) < usedBins) : #double count this in data set\n",
    "            voteData[counter]=binVote[b]\n",
    "            seatData[counter]=cumSeats[b]\n",
    "            counter +=1\n",
    "fit = np.polyfit(voteData,seatData,1)  #first-order linear regression with old polyfit\n",
    "Rsimple = fit[0]     #slope is fit[0] in y = mx + b, intercept is fit[1]\n",
    "y0 = fit[1]\n",
    "Rx = [stateGOP - 4.*stateSigma, stateGOP + 4.*stateSigma]\n",
    "Ry = [y0 + Rx[0]*Rsimple, y0 + Rx[1]*Rsimple]\n",
    "plt.plot(Rx,Ry ) \n",
    "ax.text(Rx[1]+0.02, Ry[1]+0.02, \"R = \"+str(round(Rsimple,4)), transform=ax.transAxes, fontsize=14,color='purple')\n",
    "expectedSeats = cumSeats[stateVoteBin]\n",
    "ax.text(0.02,expectedSeats+0.03,\"expected seats = \"+str(round(expectedSeats,3)),transform=ax.transAxes,fontsize=9)\n",
    "ax.text(stateGOP+0.01,0.1,\"HD statewide vote = \"+str(round(stateGOP2,3)),transform=ax.transAxes,fontsize=9)\n",
    "Ex = [0,stateGOP ]\n",
    "Ey = [expectedSeats, expectedSeats]\n",
    "plt.plot(Ex,Ey, linestyle='-.',color='red')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "ce47266f-e2ea-4649-b10c-e8225994c122",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#3/6/22 - alternate votes-to-seats with fractional seat smearing.\n",
    "# First, compute the general cdf sliver for -3 sigma to +3 sigma\n",
    "# Then, apply this smearing to the binVote weights\n",
    "seatVar = 0.04\n",
    "nBins = 1000\n",
    "nSigma = 6.  #how many total sigma of deviation we are explicitly modeling; the rest go into the tails\n",
    "nSlivers = 2*int(3*nBins*seatVar)  #budget for 3 sigma on either side of the expected vote\n",
    "sliverWt = [0.]*nSlivers  #each sliver holds the cdf reflecting the relative distance from the mean vote\n",
    "sliverSigma = [0.]*nSlivers\n",
    "totalSliverWt = 0.\n",
    "for nS in range(nSlivers):\n",
    "    dSigmaHigh = nSigma* (nS+0.5 - nSlivers/2) / float(nSlivers)\n",
    "    dSigmaLow =  nSigma* (nS-0.5 - nSlivers/2) / float(nSlivers)\n",
    "    sliverSigma[nS] = 0.5*(dSigmaHigh+dSigmaLow)  #for plotting; keeps track of this sliver's center sigma\n",
    "    sliverWt[nS] = norm.cdf(dSigmaHigh) - norm.cdf(dSigmaLow)\n",
    "    totalSliverWt += sliverWt[nS]\n",
    "lowSliverWt = 0.5 * (1. - totalSliverWt)\n",
    "highSliverWt = lowSliverWt\n",
    "#print(\"each tail of distribution has weight\",round(lowSliverWt,4) )\n",
    "#plt.plot(sliverSigma,sliverWt)\n",
    "#plt.show()\n",
    "# OK, that worked as expected.  Now, do the smearing of each bin\n",
    "smearedBinWeight = [0.]*nBins\n",
    "for b in range(nBins):\n",
    "    centerBinNo = b #int(HDvGOP[t]*nBins)   #which vote bin does this tract's vote go into for the expected statewide vote?\n",
    "    binOffset = int(nSlivers/2)\n",
    "    for nS in range(nSlivers):\n",
    "        binNo = centerBinNo + nS - binOffset\n",
    "        if (binNo < 0): #deep blue district; variance would push vote %R < 0\n",
    "            binNo = 0\n",
    "        if (binNo >= nBins):  #deep red district; variance would push vote %R > 1\n",
    "            binNo = nBins - 1\n",
    "        smearedBinWeight[binNo] += binWeight[b]*sliverWt[nS]\n",
    "    # Now put the tails into the correct bins\n",
    "    binNo = centerBinNo -1 - binOffset  #left tail\n",
    "    if binNo < 0:\n",
    "        binNo = 0\n",
    "    smearedBinWeight[binNo] += binWeight[b]*lowSliverWt\n",
    "    binNo = centerBinNo + nSlivers - binOffset  #right tail\n",
    "    if binNo >= nBins:\n",
    "        binNo = nBins -1 \n",
    "    smearedBinWeight[binNo] += binWeight[b]*highSliverWt\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(binVote, binWeight, marker='.',linestyle=\"none\",label=\"unsmeared\")\n",
    "plt.plot(binVote, smearedBinWeight, marker='o',linestyle=\"none\",label=\"smeared\")\n",
    "RANGE = [0.0, 0.5*np.max(binWeight)]\n",
    "sGOP = [stateGOP, stateGOP]\n",
    "plt.plot(sGOP,RANGE,linestyle=\"-\",label=\"statewide \"+str(round(stateGOP,3)) )\n",
    "ax.set(xlabel=\"district pct GOP\", ylabel=\"bin weight\")\n",
    "plt.legend()\n",
    "plt.show()   #this should resemble above histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "8a2d7de3-ea93-4447-bb69-36defbae38df",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with votes-to-seats, let's compute the S(V) curve with no fractional-seat smearing\n",
    "smearedBinVote = [0.]*nBins  #this will store the statewide vote for this bin\n",
    "cumSmearedVote = [0.]*nBins\n",
    "for b in range(nBins) :\n",
    "    smearedBinVote[b] = b*dV\n",
    "    cumSmearedVote[nBins-b-1] = np.sum(smearedBinWeight[:(b+1)])  #cumulative weight of all Home Districts below vote b*dV\n",
    "    # print(\"bin, bin vote, cumVote for this bin\",b,b*dV,cumVote[b] )\n",
    "    \n",
    "cumSmearedSeats = [0.]*nBins  #this will sum the seats earned for a given statewide vote\n",
    "stateVoteBin = int( (stateGOP+0.5*dV)*nBins )   #which bin (out of 1/dV) holds the statewide total vote?\n",
    "for b in range(nBins) :\n",
    "    bb = int( max(0,min(nBins-1,nBins/2 + b-stateVoteBin)) )\n",
    "    cumSmearedSeats[b] = 1. - cumSmearedVote[bb]\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.plot(smearedBinVote,cumSmearedSeats, marker='o',linestyle=\"none\",label=str(seatVar)+\" smear\")\n",
    "plt.plot(binVote, cumSeats, marker='.',linestyle=\"none\",label=\"no smear\")\n",
    "ax.set(xlabel=\"true \"+STATE+\"-wide vote=\"+str(round(stateGOP,4))+\", nBins =\"+str(nBins), ylabel=\"GOP seats won\")\n",
    "RANGE = [0.1, 0.9]\n",
    "fifty50 = [0.5, 0.5]\n",
    "expected = [stateGOP, stateGOP]\n",
    "expectedSeats = cumSeats[stateVoteBin]\n",
    "expectedS = [expectedSeats,expectedSeats]\n",
    "smearedSeats = cumSmearedSeats[stateVoteBin]\n",
    "smearedS = [smearedSeats,smearedSeats]\n",
    "plt.plot(RANGE,fifty50)\n",
    "plt.plot(fifty50,RANGE)\n",
    "plt.plot(RANGE,smearedS, linestyle=\"--\",color='blue',label=str(round(expectedSeats,3))+\"no smear\")\n",
    "plt.plot(RANGE,expectedS, linestyle=\"--\",color='orange',label=str(round(smearedSeats,3))+\"smeared\")\n",
    "plt.plot(expected,RANGE, linestyle=\"--\",color='red')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "597b7758-4f83-40f7-8909-4946e64267ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "simpler and fractional-seat-smeared (var of 0.04 ) responsiveness are 2.529 2.509\n",
      "fractional expected GOP seats =  3.797  out of  11 seats for VA\n",
      "simpler expected GOP seats =  3.7137  out of  11 seats\n"
     ]
    }
   ],
   "source": [
    "#Finally, let's compare responsiveness using smeared (fractional seat variance) to non-smeared calculated above\n",
    "#LET'S ALSO crudely ESTIMATE (smeared) RESPONSIVENESS near the STATEWIDE VOTE, as we did for non-smeared\n",
    "stateSigma = 0.03  #User-adjustable, this is the uncertainty in the statewide vote from election to election\n",
    "usedBins = int(stateSigma/dV)\n",
    "nFitPoints = 6*usedBins\n",
    "voteData = [0.]*nFitPoints\n",
    "seatData = [0.]*nFitPoints\n",
    "counter = 0\n",
    "for b in range(nBins):\n",
    "    if ( abs(b-stateVoteBin) <= 2*usedBins ):  #include this S-V pair in our line fit\n",
    "        voteData[counter]=smearedBinVote[b]\n",
    "        seatData[counter]=cumSmearedSeats[b]\n",
    "        counter += 1\n",
    "        # print(b,counter)\n",
    "        if ( abs(b-stateVoteBin) < usedBins) : #double count this in data set\n",
    "            voteData[counter]=smearedBinVote[b]\n",
    "            seatData[counter]=cumSmearedSeats[b]\n",
    "            counter +=1\n",
    "fit = np.polyfit(voteData,seatData,1)  #first-order linear regression with old polyfit\n",
    "Rsmeared = fit[0]     #slope is fit[0] in y = mx + b, intercept is fit[1]\n",
    "y0 = fit[1]\n",
    "\n",
    "print(\"simpler and fractional-seat-smeared (var of\",seatVar,\") responsiveness are\",round(Rsimple,3) ,round(Rsmeared,3) )   \n",
    "print(\"fractional expected GOP seats = \",round(nDistricts*smearedSeats,3),\" out of \",nDistricts,\"seats for\",STATE)\n",
    "print(\"simpler expected GOP seats = \",round(nDistricts*expectedSeats,4),\" out of \",nDistricts,\"seats\")\n"
   ]
  },
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   "source": []
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